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ORCIDBriefings in Bioinformatics, Volume 26
Volume 26, Number 1, 2024
- Yiwen Yang
, Chengming Zhang, Zhaonan Liu, Kazuyuki Aihara, Chuanchao Zhang, Luonan Chen, Wu Wei:
MCGAE: unraveling tumor invasion through integrated multimodal spatial transcriptomics. - Tianjiao Zhang, Xiang Zhang, Zhenao Wu, Jixiang Ren, Zhongqian Zhao, Hongfei Zhang, Guohua Wang, Tao Wang:
VGAE-CCI: variational graph autoencoder-based construction of 3D spatial cell-cell communication network. - Xiaoyi Li, Kangli Zhu, Ying Zhen:
A versatile pipeline to identify convergently lost ancestral conserved fragments associated with convergent evolution of vocal learning. - Zhen Wang, Yizhen Feng, Qingwen Tian, Ziqi Liu, Pengju Yan, Xiaolin Li:
RNADiffFold: generative RNA secondary structure prediction using discrete diffusion models. - James Strudwick, Laura-Jayne Gardiner, Kate Denning-James, Niina Haiminen, Ashley Evans, Jennifer Kelly, Matthew Madgwick, Filippo Utro, Ed Seabolt, Christopher Gibson, Bharat Bedi, Daniel Clayton, Ciaron Howell, Laxmi Parida, Anna Paola Carrieri:
AutoXAI4Omics: an automated explainable AI tool for omics and tabular data. - Xin Ma, Lijing Lin, Qian Zhao, Mudassar Iqbal:
TriTan: an efficient triple nonnegative matrix factorization method for integrative analysis of single-cell multiomics data. - Anna Postovskaya, Koen Vercauteren, Pieter Meysman, Kris Laukens:
tcrBLOSUM: an amino acid substitution matrix for sensitive alignment of distant epitope-specific TCRs. - Jiachen Chen, Joanne M. Murabito, Kathryn L. Lunetta:
ONDSA: a testing framework based on Gaussian graphical models for differential and similarity analysis of multiple omics networks. - Yinhu Li, Guangze Pan, Shuai Wang, Zhengtu Li, Ru Yang, Yiqi Jiang, Yu Chen, Shuaicheng Li, Bairong Shen:
Comprehensive human respiratory genome catalogue underlies the high resolution and precision of the respiratory microbiome. - Saurav Chandra Das, Wahia Tasnim, Humayan Kabir Rana, Uzzal Kumar Acharjee, Md. Manowarul Islam, Rabea Khatun:
Comprehensive bioinformatics and machine learning analyses for breast cancer staging using TCGA dataset. - Alfred Ultsch, Jörn Lötsch:
Augmenting small biomedical datasets using generative AI methods based on self-organizing neural networks. - Yuqi Miao, Huang Xu, Shuang Wang:
PartIES: a disease subtyping framework with Partition-level Integration using diffusion-Enhanced Similarities from multi-omics Data. - Elisabet Munté, Carla Roca, Jesús del Valle, Lidia Feliubadaló, Marta Pineda, Bernat Gel, Elisabeth Castellanos, Barbara Rivera, David Cordero, Víctor Moreno, Conxi Lázaro, José Marcos Moreno-Cabrera:
Detection of germline CNVs from gene panel data: benchmarking the state of the art. - Yuhan Wang, Zhikang Wang, Xuan Yu, Xiaoyu Wang, Jiangning Song, Dong-Jun Yu, Fang Ge:
MORE: a multi-omics data-driven hypergraph integration network for biomedical data classification and biomarker identification. - Hai Cui, Meiyu Duan, Haijia Bi, Xiaobo Li, Xiaodi Hou, Yi-Jia Zhang:
Heterogeneous graph contrastive learning with gradient balance for drug repositioning. - Sara Cuvertino, Terence Garner, Evgenii Martirosian, Bridgious Walusimbi, Susan J. Kimber, Siddharth Banka, Adam Stevens:
Higher order interaction analysis quantifies coordination in the epigenome revealing novel biological relationships in Kabuki syndrome. - Marin Volaric, Nevenka Mestrovic, Evelin Despot-Slade:
SatXplor - a comprehensive pipeline for satellite DNA analyses in complex genome assemblies. - Correction to: HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction.
- Junning Feng, Yong Liang, Tianwei Yu:
ADM: adaptive graph diffusion for meta-dimension reduction. - Yuejun Tan, Linhai Xie, Hong Yang, Qingyuan Zhang, Jinyuan Luo, Yanchun Zhang:
BioDSNN: a dual-stream neural network with hybrid biological knowledge integration for multi-gene perturbation response prediction. - Yuxiao Wei, Qi Zhang, Liwei Liu:
The improved de Bruijn graph for multitask learning: predicting functions, subcellular localization, and interactions of noncoding RNAs. - Long Xu, Qiang Yang, Weihe Dong, Xiaokun Li, Kuanquan Wang, Suyu Dong, Xianyu Zhang, Tiansong Yang, Gongning Luo, Xingyu Liao, Xin Gao, Guohua Wang:
Meta learning for mutant HLA class I epitope immunogenicity prediction to accelerate cancer clinical immunotherapy. - Leandro Murgas, Gianluca Pollastri, Erick Riquelme, Mauricio Sáez, Alberto J. M. Martin:
Understanding relationships between epigenetic marks and their application to robust assignment of chromatin states. - Ivan Ferrari, Federica De Grossi, Giancarlo Lai, Stefania Oliveto, Giorgia Deroma, Stefano Biffo, Nicola Manfrini:
CancerHubs: a systematic data mining and elaboration approach for identifying novel cancer-related protein interaction hubs. - Xiaolong Zhang, Xianchao Ji, Lingxiang Wang, Lianjiang Chi, Chengtao Li, Shaoqing Wen, Hua Chen:
STRsensor: a computationally efficient method for STR allele-typing from massively parallel sequencing data. - Expression of Concern: Bioinformatics in Russia: history and present-day landscape.
- Yunlong Wang, Siyuan Kong, Cong Zhou, Yanfang Wang, Yubo Zhang, Yaping Fang, Guoliang Li:
A review of deep learning models for the prediction of chromatin interactions with DNA and epigenomic profiles. - Shuailin Xue, Fangfang Zhu, Jinyu Chen, Wenwen Min:
Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location, and histology using GCN. - Tong Lu, Wei Guo, Wei Guo, Wangyang Meng, Tianyi Han, Zizhen Guo, Chengqiang Li, Shugeng Gao, Youqiong Ye, Hecheng Li:
A novel computational model ITHCS for enhanced prognostic risk stratification in ESCC by correcting for intratumor heterogeneity. - Hao Yuan, Parker Hicks, Mansooreh Ahmadian, Kayla A. Johnson, Lydia Valtadoros, Arjun Krishnan:
Annotating publicly-available samples and studies using interpretable modeling of unstructured metadata. - Zhenxian Zheng, Yingxuan Ren, Lei Chen, Angel On Ki Wong, Shumin Li, Xian Yu, Tak Wah Lam, Ruibang Luo:
Repun: an accurate small variant representation unification method for multiple sequencing platforms. - Tianyu Liu, Wenxin Long, Zhiyuan Cao, Yuge Wang, Chuan Hua He, Le Zhang, Stephen M. Strittmatter, Hongyu Zhao:
CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis. - Fatma S. Ahmed, Saleh K. H. Aly, Xiangrong Liu:
NABP-BERT: NANOBODY®-antigen binding prediction based on bidirectional encoder representations from transformers (BERT) architecture. - Yong Liu, Le Zhong, Bin Yan, Zhuobin Chen, Yanjia Yu, Dan Yu, Jing Qin, Junwen Wang:
A self-attention-driven deep learning framework for inference of transcriptional gene regulatory networks. - Lu-Bin Cui, Guiliang Guo, Michael K. Ng, Quan Zou, Yushan Qiu:
GSTRPCA: irregular tensor singular value decomposition for single-cell multi-omics data clustering. - Zheyu Ding, Rong Wei, Jianing Xia, Yonghao Mu, Jiahuan Wang, Yingying Lin:
Exploring the potential of large language model-based chatbots in challenges of ribosome profiling data analysis: a review. - Mengya Liu, Zhan-Li Sun, Zhigang Zeng, Kin-Man Lam:
Multi-kernel feature extraction with dynamic fusion and downsampled residual feature embedding for predicting rice RNA N6-methyladenine sites. - Aimin Xie, Hao Wang, Jiaxu Zhao, Zhaoyang Wang, Jinyuan Xu, Yan Xu:
scPAS: single-cell phenotype-associated subpopulation identifier. - Xizi Luo, Amadeus Song Yi Chi, Andre Huikai Lin, Tze Jet Ong, Limsoon Wong, Chowdhury Rafeed Rahman:
Benchmarking recent computational tools for DNA-binding protein identification. - Ornit Nahman, Timothy J. Few-Cooper, Shai S. Shen-Orr:
Cell-specific priors rescue differential gene expression in spatial spot-based technologies. - Xinglong Wang, Kangjie Xu, Lingling Ma, Ruoxi Sun, Kun Wang, Ruiyan Wang, Junli Zhang, Wenwen Tao, Kai Linghu, Shuyao Yu, Jingwen Zhou:
Diffusion model assisted designing self-assembling collagen mimetic peptides as biocompatible materials. - Bo Wang, Yahui Long, Yuting Bai, Jiawei Luo, Chee Keong Kwoh:
STCGAN: a novel cycle-consistent generative adversarial network for spatial transcriptomics cellular deconvolution. - Boya Ji, Xiaoqi Wang, Xiang Wang, Liwen Xu, Shaoliang Peng:
scDCA: deciphering the dominant cell communication assembly of downstream functional events from single-cell RNA-seq data. - Correction to: Toward molecular diagnosis of major depressive disorder by plasma peptides using a deep learning approach.
- Konstantina Tzavella, Adrián Díaz, Catharina Olsen, Wim F. Vranken:
Combining evolution and protein language models for an interpretable cancer driver mutation prediction with D2Deep. - Cathal Ormond, Niamh M. Ryan, Mathieu Cap, William Byerley, Aiden P. Corvin, Elizabeth A. Heron:
BICEP: Bayesian inference for rare genomic variant causality evaluation in pedigrees. - Tianjiao Zhang, Hao Sun, Zhenao Wu, Zhongqian Zhao, Xingjie Zhao, Hongfei Zhang, Bo Gao, Guohua Wang:
GAADE: identification spatially variable genes based on adaptive graph attention network. - Shan Tharanga, Eyyüb Selim Ünlü, Yongli Hu, Muhammad Farhan Sjaugi, Muhammet A Çelik, Hilal Hekimoglu, Olivo Miotto, Muhammed Miran Öncel, Asif M. Khan:
DiMA: sequence diversity dynamics analyser for viruses. - Shyamsundar Ravishankar, Vilma Perez, Roberta Davidson, Xavier Roca-Rada, Divon Lan, Yassine Souilmi, Bastien Llamas:
Filtering out the noise: metagenomic classifiers optimize ancient DNA mapping. - Cui-Xiang Lin, Hong-Dong Li, Jianxin Wang:
LIMO-GCN: a linear model-integrated graph convolutional network for predicting Alzheimer disease genes. - Yan-Yu Li, Fengcui Qian, Guo-Rui Zhang, Xue-Cang Li, Li-Wei Zhou, Zheng-Min Yu, Wei Liu, Qiu-Yu Wang, Chunquan Li:
FunlncModel: integrating multi-omic features from upstream and downstream regulatory networks into a machine learning framework to identify functional lncRNAs. - Xueshi Yu, Renmin Han, Haitao Jiao, Wenjia Meng:
Few-shot classification of Cryo-ET subvolumes with deep Brownian distance covariance. - Xiaolong Wu, Lehan Zhang, Xiaochu Tong, Yitian Wang, Zimei Zhang, Xiangtai Kong, Shengkun Ni, Xiaomin Luo, Mingyue Zheng, Yun Tang, Xutong Li:
miCGR: interpretable deep neural network for predicting both site-level and gene-level functional targets of microRNA. - Shuhe Liu, Zhen Wei, Daniel F. Carr, John Moraros:
Deciphering the genetic interplay between depression and dysmenorrhea: a Mendelian randomization study. - Peng Liu, Yuchen Pan, Hung-Ching Chang, Wenjia Wang, Yusi Fang, Xiangning Xue, Jian Zou, Jessica M. Toothaker, Oluwabunmi Olaloye, Eduardo Gonzalez Santiago, Black McCourt, Vanessa Mitsialis, Pietro Presicce, Suhas G. Kallapur, Scott B. Snapper, Jia-Jun Liu, George C. Tseng, Liza Konnikova, Silvia Liu:
Comprehensive evaluation and practical guideline of gating methods for high-dimensional cytometry data: manual gating, unsupervised clustering, and auto-gating. - Yixuan Wang, Yanfang Guan, Xin Lai, Yuqian Liu, Zhili Chang, Xiaonan Wang, Quan Wang, Jingjing Liu, Jian Zhao, Shuanying Yang, Jiayin Wang, Xiaofeng Song:
THOR: a TMB heterogeneity-adaptive optimization model predicts immunotherapy response using clonal genomic features in group-structured data. - Junhang Cao, Jun Zhang, Qiyuan Yu, Junkai Ji, Jianqiang Li, Shan He, Zexuan Zhu:
TG-CDDPM: text-guided antimicrobial peptides generation based on conditional denoising diffusion probabilistic model. - Yunjian Chang, Ligang Wu:
CapHLA: a comprehensive tool to predict peptide presentation and binding to HLA class I and class II. - Pawel Dudzic, Bartosz Janusz, Tadeusz Satlawa, Dawid Chomicz, Tomasz Gawlowski, Rafal Grabowski, Przemek Józwiak, Mateusz Tarkowski, Maciej Mycielski, Sonia Wróbel, Konrad Krawczyk:
RIOT - Rapid Immunoglobulin Overview Tool - annotation of nucleotide and amino acid immunoglobulin sequences using an open germline database. - Junlei Liao, Hongyang Yi, Hao Wang, Sumei Yang, Duanmei Jiang, Xin Huang, Mingxia Zhang, Jiayin Shen, Hongzhou Lu, Yuanling Niu:
CDCM: a correlation-dependent connectivity map approach to rapidly screen drugs during outbreaks of infectious diseases. - Sergio Llaneza-Lago, William D. Fraser, Darrell Green:
Bayesian unsupervised clustering identifies clinically relevant osteosarcoma subtypes. - Dries Heylen, Murih Pusparum, Jurgis Kuliesius, Jim Wilson, Young-Chan Park, Jacek Jamiolkowski, Valentino D'onofrio, Dirk Valkenborg, Jan Aerts, Gökhan Ertaylan, Jef Hooyberghs:
Synthetic plasma pool cohort correction for affinity-based proteomics datasets allows multiple study comparison. - Yi Zhang, Yin Wang, Xinyuan Liu, Xi Feng:
CPARI: a novel approach combining cell partitioning with absolute and relative imputation to address dropout in single-cell RNA-seq data. - Nana Jin, Chuanchuan Nan, Wanyang Li, Peijing Lin, Yu Xin, Jun Wang, Yuelong Chen, Yuanhao Wang, Kaijiang Yu, Changsong Wang, Chunbo Chen, Qingshan Geng, Lixin Cheng:
PAGE-based transfer learning from single-cell to bulk sequencing enhances model generalization for sepsis diagnosis. - Qianwen Luo, Shanshan Zhang, Hamza Butt, Yin Chen, Hongmei Jiang, Lingling An:
PhyImpute and UniFracImpute: two imputation approaches incorporating phylogeny information for microbial count data. - Ankang Wei, Zhen Xiao, Lingling Fu, Weizhong Zhao, Xingpeng Jiang:
Predicting phage-host interactions via feature augmentation and regional graph convolution. - Chi Zhang, Yiran Cheng, Kaiwen Feng, Fa Zhang, Renmin Han, Jieqing Feng:
UPicker: a semi-supervised particle picking transformer method for cryo-EM micrographs. - Willem Stock, Coralie Rousseau, Glen Dierickx, Sofie D'hondt, Luz Amadei Martínez, Simon M. Dittami, Luna M. van der Loos, Olivier De Clerck:
Breaking free from references: a consensus-based approach for community profiling with long amplicon nanopore data. - Junwei Luo, Jiaojiao Wang, Jingjing Wei, Chaokun Yan, Huimin Luo:
DeepHapNet: a haplotype assembly method based on RetNet and deep spectral clustering. - Runqing Wang, Qiguo Dai, Xiaodong Duan, Quan Zou:
stHGC: a self-supervised graph representation learning for spatial domain recognition with hybrid graph and spatial regularization. - Lin Yuan, Shengguo Sun, Yufeng Jiang, Qinhu Zhang, Lan Ye, Chun-Hou Zheng, De-Shuang Huang:
scRGCL: a cell type annotation method for single-cell RNA-seq data using residual graph convolutional neural network with contrastive learning. - Jiaqi Wang, Ronggang Xi, Yi Wang, Huiyuan Gao, Ming Gao, Xiaozhe Zhang, Lihua Zhang, Yukui Zhang:
Toward molecular diagnosis of major depressive disorder by plasma peptides using a deep learning approach. - Zexuan Wang, Qipeng Zhan, Shu Yang, Shizhuo Mu, Jiong Chen, Sumita Garai, Patryk Orzechowski, Joost B. Wagenaar, Li Shen:
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics. - Sehi Park, Kil To Chong, Hilal Tayara:
CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites. - Jiajian Luo, Jiye Fu, Zuhong Lu, Jing Tu:
Deep learning in integrating spatial transcriptomics with other modalities. - Mingguang Shi, Xuefeng Li:
Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL. - Xianliang Liu, Jiawei Luo, Xinyan Wang, Yang Zhang, Junjie Chen:
Directed evolution of antimicrobial peptides using multi-objective zeroth-order optimization. - Ren Wang, Qiumei Liu, Wenhua You, Huiyu Wang, Yun Chen:
A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma. - Sara Potente, Diego Boscarino, Dino Paladin, Sergio Marchini, Luca Beltrame, Chiara Romualdi:
SAMURAI: shallow analysis of copy number alterations using a reproducible and integrated bioinformatics pipeline. - Meng-Chi Chung, Li-Jen Su, Chien-Lin Chen, Li-Ching Wu:
Revealing the antimicrobial potential of traditional Chinese medicine through text mining and molecular computation. - George Assaf, Fei Liu, Monika Heiner:
Incremental modelling and analysis of biological systems with fuzzy hybrid Petri nets. - Le Yang, Runpu Chen, Steve Goodison, Yijun Sun:
A comprehensive benchmark study of methods for identifying significantly perturbed subnetworks in cancer. - José A. Sánchez-Villanueva, Lia N'guyen, Mathilde Poplineau, Estelle Duprez, Elisabeth Remy, Denis Thieffry:
Predictive modelling of acute Promyelocytic leukaemia resistance to retinoic acid therapy. - Xiaoqing Ru, Shulin Zhao, Quan Zou, Lifeng Xu:
Identify potential drug candidates within a high-quality compound search space. - Uwaise Ibna Islam, Andre Luiz Campelo dos Santos, Ria Kanjilal, Raquel Assis:
Learning genotype-phenotype associations from gaps in multi-species sequence alignments. - Wendong Huang, Yaofeng Hu, Lequn Wang, Guangsheng Wu, Chuanchao Zhang, Qianqian Shi:
Spatially aligned graph transfer learning for characterizing spatial regulatory heterogeneity. - Jordi Martorell-Marugan, Raúl López-Domínguez, Juan Antonio Villatoro-García, Daniel Toro-Domínguez, Marco Chierici, Giuseppe Jurman, Pedro Carmona-Saez:
Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics. - Yonathan Schwammenthal, Tom Rabinowitz, Lina Basel-Salmon, Reut Tomashov-Matar, Noam Shomron:
Noninvasive fetal genotyping using deep neural networks. - Ashwin Dhakal, Rajan Gyawali, Liguo Wang, Jianlin Cheng:
Artificial intelligence in cryo-EM protein particle picking: recent advances and remaining challenges. - Baiming Zou, James G. Xenakis, Meisheng Xiao, Apoena Aguiar Ribeiro, Kimon Divaris, Di Wu, Fei Zou:
A deep learning feature importance test framework for integrating informative high-dimensional biomarkers to improve disease outcome prediction. - Ashwin R. Nair, Xingjian Li, Bhupendra Solanki, Souradeep Mukhopadhyay, Ankit Jha, Mostofa Rafid Uddin, Mainak Singha, Biplab Banerjee, Min Xu:
Towards molecular structure discovery from cryo-ET density volumes via modelling auxiliary semantic prototypes. - Yang Yang, Zixuan Zheng, Yuyang Xu, Huifang Wei, Wenying Yan:
BioGSF: a graph-driven semantic feature integration framework for biomedical relation extraction. - Alida Zárate, Lorena Díaz-González, Blanca Taboada:
VirDetect-AI: a residual and convolutional neural network-based metagenomic tool for eukaryotic viral protein identification. - Quan Lu, Jiajun Xu, Renyi Zhang, Hangcheng Liu, Meng Wang, Xiaoshuang Liu, Zhenyu Yue, Yujia Gao:
RiceSNP-ABST: a deep learning approach to identify abiotic stress-associated single nucleotide polymorphisms in rice. - Mianyan Li, Thomas Hall, David E. MacHugh, Liang Chen, Dorian Garrick, Lixian Wang, Fuping Zhao:
KPRR: a novel machine learning approach for effectively capturing nonadditive effects in genomic prediction. - Giuseppe Defazio, Marco Antonio Tangaro, Graziano Pesole, Bruno Fosso:
kMetaShot: a fast and reliable taxonomy classifier for metagenome-assembled genomes. - Fu Liu, Zhimiao Zhao, Yun Liu:
PHPGAT: predicting phage hosts based on multimodal heterogeneous knowledge graph with graph attention network. - Shijie Luo, Ming Zhu, Liquan Lin, Jiajing Xie, Shihao Lin, Ying Chen, Jiali Zhu, Jialiang Huang:
DECA: harnessing interpretable transformer model for cellular deconvolution of chromatin accessibility profile. - Correction to: BANMF-S: a blockwise accelerated non-negative matrix factorization framework with structural network constraints for single cell imputation.
- Xianxiao Zhou, Ling Wu, Minghui Wang, Guojun Wu, Bin Zhang:
iDOMO: identification of drug combinations via multi-set operations for treating diseases. - Cristian Riccio, Max L. Jansen, Felix Thalén, Georgios Koliopanos, Vivian Link, Andreas Ziegler:
Assessment of the functionality and usability of open-source rare variant analysis pipelines. - Matee Ullah, Shahid Akbar, Ali Raza, Kashif Ahmad Khan, Quan Zou:
TargetCLP: clathrin proteins prediction combining transformed and evolutionary scale modeling-based multi-view features via weighted feature integration approach. - Kaiyuan Yang, Jiabei Cheng, Shenghao Cao, Xiaoyong Pan, Hong-Bin Shen, Ye Yuan:
Predicting transcriptional changes induced by molecules with MiTCP. - Hao Lu, Mostafa Rezapour, Haseebullah Baha, Muhammad Khalid Khan Niazi, Aarthi Narayanan, Metin Nafi Gürcan:
Classification-based pathway analysis using GPNet with novel P-value computation. - Xingyi Li, Jialuo Xu, Junming Li, Jia Gu, Xuequn Shang:
Towards simplified graph neural networks for identifying cancer driver genes in heterophilic networks. - Donghan Wang, Xu Dong, Xueyou Zhang, Lihong Hu:
GADIFF: a transferable graph attention diffusion model for generating molecular conformations. - Jiaojiao Guan, Yongxin Ji, Cheng Peng, Wei Zou, Xubo Tang, Jiayu Shang, Yanni Sun:
GOPhage: protein function annotation for bacteriophages by integrating the genomic context. - Correction to: STCGAN: a novel cycle-consistent generative adversarial network for spatial transcriptomics cellular deconvolution.
- Huan Yang, Minglei Yang, Jiani Chen, Guocong Yao, Quan Zou, Linpei Jia:
Multimodal deep learning approaches for precision oncology: a comprehensive review. - Peng-Hsuan Li, Yih-Yun Sun, Hsueh-Fen Juan, Chien-Yu Chen, Huai-Kuang Tsai, Jia-Hsin Huang:
A large language model framework for literature-based disease-gene association prediction. - Qiqi Lu, Zhixian Liu, Xiaosheng Wang:
Inferring tumor purity using multi-omics data based on a uniform machine learning framework MoTP. - Liu Yang, Suqi Cao, Lei Liu, Ruixin Zhu, Dingfeng Wu:
cyclicpeptide: a Python package for cyclic peptide drug design. - Wenjie Sun, Daphne van Ginneken, Leïla Perié:
scMitoMut for calling mitochondrial lineage-related mutations in single cells. - Han Wang, Zilin Ren, Jinghong Sun, Yongbing Chen, Xiaochen Bo, Jiguo Xue, Jingyang Gao, Ming Ni:
DeepPFP: a multi-task-aware architecture for protein function prediction. - Upamanyu Ghose, William Sproviero, Laura Winchester, Najaf Amin, Taiyu Zhu, Danielle Newby, Brittany S. Ulm, Angeliki Papathanasiou, Liu Shi, Qiang Liu, Marco Fernandes, Cassandra Adams, Ashwag Albukhari, Majid Almansouri, Hani Choudhry, Cornelia van Duijn, Alejo J. Nevado-Holgado:
Genome-wide association neural networks identify genes linked to family history of Alzheimer's disease. - Zheyang Zhang, Ronghan Tang, Ming Zhu, Zhijuan Zhu, Jiali Zhu, Hua Li, Mengsha Tong, Nainong Li, Jialiang Huang:
Deciphering cell states and the cellular ecosystem to improve risk stratification in acute myeloid leukemia. - Lan Cao, Wenhao Zhang, Fan Yang, Shengquan Chen, Xiaobing Huang, Feng Zeng, Ying Wang:
BIOTIC: a Bayesian framework to integrate single-cell multi-omics for transcription factor activity inference and improve identity characterization of cells. - Yiren Shao, Qi Gao, Liuyang Wang, Dongmei Li, Andrew B. Nixon, Cliburn Chan, Qi-Jing Li, Jichun Xie:
B-Lightning: using bait genes for marker gene hunting in single-cell data with complex heterogeneity. - Marco Antônio M. Pretti, Gustavo Fioravanti Vieira, Mariana Boroni, Martín H. Bonamino:
Unveiling cross-reactivity: implications for immune response modulation in cancer. - Xiangnan Xu, Alistair M. Senior, David G. Le Couteur, Victoria C. Cogger, David Raubenheimer, David E. James, Benjamin Parker, Stephen J. Simpson, Samuel Müller, Jean Y. H. Yang:
eNODAL: an experimentally guided nutriomics data clustering method to unravel complex drug-diet interactions. - Correction to: Unveiling cross-reactivity: implications for immune response modulation in cancer.
- Qi-Xin Zhang, Tianneng Zhu, Feng Lin, Dunhuang Fang, Xuejun Chen, Xiangyang Lou, Zhijun Tong, Bingguang Xiao, Hai-Ming Xu:
mmGEBLUP: an advanced genomic prediction scheme for genetic improvement of complex traits in crops through integrative analysis of major genes, polygenes, and genotype-environment interactions. - Abdallah Derbalah, Masoud Jamei, Iain Gardner, Armin Sepp:
The role of automation in enhancing reproducibility and interoperability of PBPK models. - Jin Han, Haohong Zhang, Kang Ning:
Techniques for learning and transferring knowledge for microbiome-based classification and prediction: review and assessment. - Sangmin Seo, Hwanhee Kim, Jieun Lee, Seungyeon Choi, Sanghyun Park:
Exploring the potential of compound-protein complex structure-free models in virtual screening using BlendNet. - Bo Yang, Chenxi Cui, Meng Wang, Hong Ji, Feiyue Gao:
Multi-view multi-level contrastive graph convolutional network for cancer subtyping on multi-omics data. - Luca Cattelani, Vittorio Fortino:
Dual-stage optimizer for systematic overestimation adjustment applied to multi-objective genetic algorithms for biomarker selection. - Qiaolin Lu, Jiayuan Ding, Lingxiao Li, Yi Chang:
Graph contrastive learning of subcellular-resolution spatial transcriptomics improves cell type annotation and reveals critical molecular pathways. - Lijun Cai, Guanyu Yue, Yifan Chen, Li Wang, Xiaojun Yao, Quan Zou, Xiangzheng Fu, Dong-Sheng Cao:
ET-PROTACs: modeling ternary complex interactions using cross-modal learning and ternary attention for accurate PROTAC-induced degradation prediction. - You Wu, Pengfei Xu, Liyuan Wang, Shuai Liu, Yingnan Hou, Hui Lu, Peng Hu, Xiaofei Li, Xiang Yu:
scGO: interpretable deep neural network for cell status annotation and disease diagnosis. - Jing Liang, Zhuo Hu, Ying Bi, Han Cheng, Weifeng Guo:
Multimodal multiobjective optimization with structural network control principles to optimize personalized drug targets for drug discovery of individual patients. - Olivier Cinquin:
Steering veridical large language model analyses by correcting and enriching generated database queries: first steps toward ChatGPT bioinformatics. - Lingpeng Kong, Hong Cheng, Kun Zhu, Bo Song:
LOGOWheat: deep learning-based prediction of regulatory effects for noncoding variants in wheats. - Nandhini Rajagopal, Udit Choudhary, Kenny Tsang, Kyle P. Martin, Murat Karadag, Hsin-Ting Chen, Na-Young Kwon, Joseph Mozdzierz, Alexander M. Horspool, Li Li, Peter M. Tessier, Michael S. Marlow, Andrew E. Nixon, Sandeep Kumar:
Deep learning-based design and experimental validation of a medicine-like human antibody library. - Xikang Feng, Miaozhe Huo, He Li, Yongze Yang, Yuepeng Jiang, Liang He, Shuai Cheng Li:
A comprehensive benchmarking for evaluating TCR embeddings in modeling TCR-epitope interactions. - Iljung Jin, Songyeon Lee, Martin Schmuhalek, Hojung Nam:
DD-PRiSM: a deep learning framework for decomposition and prediction of synergistic drug combinations. - Ruiqian Yao, Lu Sun, Ruifang Gao, Yue Mei, Geng Xue, Dong Yu:
PTTM: dissecting the profile of tumor tissue microbiome to reveal microbiota features and associations with host transcriptome. - Xintian Xu, Rui Li, Ouyang Mo, Kai Liu, Justin Li, Pei Hao:
Cell-type deconvolution for bulk RNA-seq data using single-cell reference: a comparative analysis and recommendation guideline. - Ansar Naseem, Fahad Alturise, Tamim Alkhalifah, Yaser Daanial Khan:
ESM-BBB-Pred: a fine-tuned ESM 2.0 and deep neural networks for the identification of blood-brain barrier peptides. - Dian Meng, Yu Feng, Kaishen Yuan, Zitong Yu, Qin Cao, Lixin Cheng, Xubin Zheng:
scMMAE: masked cross-attention network for single-cell multimodal omics fusion to enhance unimodal omics. - Cheng Han, Shanshan Fu, Miaomiao Chen, Yujie Gou, Dan Liu, Chi Zhang, Xinhe Huang, Leming Xiao, Miaoying Zhao, Jiayi Zhang, Qiang Xiao, Di Peng, Yu Xue:
GPSD: a hybrid learning framework for the prediction of phosphatase-specific dephosphorylation sites. - Shilong Wang, Hai Cui, Yanchen Qu, Yijia Zhang:
Multi-source biological knowledge-guided hypergraph spatiotemporal subnetwork embedding for protein complex identification. - Liguo Ye, Cheng Ye, Pengtao Li, Yu Wang, Wenbin Ma:
Inferring the genetic relationships between unsupervised deep learning-derived imaging phenotypes and glioblastoma through multi-omics approaches. - Elissavet Zacharopoulou, Maria D. Paraskevopoulou, Spyros Tastsoglou, Athanasios Alexiou, Anna Karavangeli, Vasileios Pierros, Stefanos Digenis, Galatea Mavromati, Artemis G. Hatzigeorgiou, Dimitra Karagkouni:
microT-CNN: an avant-garde deep convolutional neural network unravels functional miRNA targets beyond canonical sites. - Yiyang Zhu, Wenying Chen, Kexuan Zhu, Yuxin Liu, Shuiping Huang, Ping Zeng:
Polygenic prediction for underrepresented populations through transfer learning by utilizing genetic similarity shared with European populations. - Yuanyuan Mo, Juan Liu, Lihua Zhang:
Deconvolution of spatial transcriptomics data via graph contrastive learning and partial least square regression. - Tianjiao Zhang, Zhongqian Zhao, Jixiang Ren, Ziheng Zhang, Hongfei Zhang, Guohua Wang:
cfDiffusion: diffusion-based efficient generation of high quality scRNA-seq data with classifier-free guidance. - Geyan Ye, Xibao Cai, Houtim Lai, Xing Wang, Junhong Huang, Longyue Wang, Wei Liu, Xiangxiang Zeng:
DrugAssist: a large language model for molecule optimization. - Yinqiao Yan, Xiangyu Luo:
BACT: nonparametric Bayesian cell typing for single-cell spatial transcriptomics data. - Kris Sankaran, Saritha Kodikara, Jingyi Jessica Li, Kim-Anh Lê Cao:
Semisynthetic simulation for microbiome data analysis. - Genhui Zheng, Dingfeng Wu, Xiuxia Wei, Dongpo Xu, Tiantian Mao, Deyu Yan, Wenhao Han, Xiaoxiao Shang, Zikun Chen, Jingxuan Qiu, Kailin Tang, Zhiwei Cao, Tianyi Qiu:
PbsNRs: predict the potential binders and scaffolds for nuclear receptors. - Yixuan Qiao, Hong Zhou, Yang Liu, Ruixuan Chen, Xiaodong Zhang, Sheng Nie, Fan Fan Hou, Yi Zhao, Xin Xu, Lianhe Zhao:
A multi-modal fusion model with enhanced feature representation for chronic kidney disease progression prediction. - Siwei Wu, Chaoyi Yin, Yuezhu Wang, Huiyan Sun:
Identifying cancer prognosis genes through causal learning. - Sushmita Basu, Jing Yu, Daisuke Kihara, Lukasz A. Kurgan:
Twenty years of advances in prediction of nucleic acid-binding residues in protein sequences. - Juntao Li, Shan Xiang, Dongqing Wei:
Deciphering progressive lesion areas in breast cancer spatial transcriptomics via TGR-NMF. - Hui Li, Lu Meng, Hongke Wang, Liang Cui, Heyu Sheng, Peiyan Zhao, Shuo Hong, Xinhua Du, Shi Yan, Yun Xing, Shicheng Feng, Yan Zhang, Huan Fang, Jing Bai, Yan Liu, Shaowei Lan, Tao Liu, Yanfang Guan, Xuefeng Xia, Xin Yi, Ying Cheng:
Precise identification of somatic and germline variants in the absence of matched normal samples. - Lingsheng Cai, Xiuli Ma, Jianzhu Ma:
Integrating scRNA-seq and scATAC-seq with inter-type attention heterogeneous graph neural networks. - Qiongyi Zhao, Woo Jun Shim, Yuliangzi Sun, Enakshi Sinniah, Sophie Shen, Mikael Bodén, Nathan J. Palpant:
TRIAGE: an R package for regulatory gene analysis. - Hong Xia, Boya Ji, Debin Qiao, Shaoliang Peng:
CellMsg: graph convolutional networks for ligand-receptor-mediated cell-cell communication analysis. - Aoyi Wang, Haoyang Peng, Yingdong Wang, Haoran Zhang, Caiping Cheng, Jinzhong Zhao, Wuxia Zhang, Jianxin Chen, Peng Li:
NP-TCMtarget: a network pharmacology platform for exploring mechanisms of action of traditional Chinese medicine. - Yiwen Wei, Tianyi Qiu, Yisi Ai, Yuxi Zhang, Junting Xie, Dong Zhang, Xiaochuan Luo, Xiulan Sun, Xin Wang, Jingxuan Qiu:
Advances of computational methods enhance the development of multi-epitope vaccines. - Lixian Lin, Haoyu Wang, Yuxiao Chen, Yuanyuan Wang, Yujie Xu, Zhenglin Chen, Yuemin Yang, Kunpeng Liu, Xiaokai Ma:
STMGraph: spatial-context-aware of transcriptomes via a dual-remasked dynamic graph attention model. - Yanming Wei, Tong Zhou, Yixiao Zhai, Liang Yu, Quan Zou:
FORAlign: accelerating gap-affine DNA pairwise sequence alignment using FOR-blocks based on Four Russians approach with linear space complexity. - Elena Domínguez Romero, Stanislav Mazurenko, Martin Scheringer, Vítor A. P. Martins dos Santos, Chris T. A. Evelo, Mihail Anton, John M. Hancock, Anze Zupanic, María Suárez-Diez:
Response to Letter to Editor by A. Derbalah et al.: the role of automation in enhancing reproducibility and interoperability of PBPK models. - Raúl Galindo-Hernández, Katya Rodríguez-Vázquez, Edgardo Galán-Vásquez, Carlos Ignacio Hernández Castellanos:
Online-adjusted evolutionary biclustering algorithm to identify significant modules in gene expression data. - Xiangfei Zhou, Hao Wu:
scHiClassifier: a deep learning framework for cell type prediction by fusing multiple feature sets from single-cell Hi-C data. - Ashok Kumar, Sonia Chadha, Mradul Sharma, Mukesh Kumar:
Deciphering optimal molecular determinants of non-hemolytic, cell-penetrating antimicrobial peptides through bioinformatics and Random Forest. - Nanhai Jiang, Yang Wu, Steven G. Rozen:
Benchmarking 13 tools for mutational signature attribution, including a new and improved algorithm. - Yueer Li, Chen Peng, Fei Chi, Zinuo Huang, Mengyi Yuan, Xin Zhou, Chao Jiang:
The iPhylo suite: an interactive platform for building and annotating biological and chemical taxonomic trees. - Cheng Tan, Yijie Zhang, Zhangyang Gao, Hanqun Cao, Siyuan Li, Siqi Ma, Mathieu Blanchette, Stan Z. Li:
R3Design: deep tertiary structure-based RNA sequence design and beyond. - Si Zheng, Yaowen Gu, Yuzhen Gu, Yelin Zhao, Liang Li, Min Wang, Rui Jiang, Xia Yu, Ting Chen, Jiao Li:
Machine learning-enabled virtual screening indicates the anti-tuberculosis activity of aldoxorubicin and quarfloxin with verification by molecular docking, molecular dynamics simulations, and biological evaluations. - Kaiwen Zhang, Yuhao Tao, Fei Wang:
AntiBinder: utilizing bidirectional attention and hybrid encoding for precise antibody-antigen interaction prediction. - Sanjana Tule, Gabriel Foley, Mikael Bodén:
Do protein language models learn phylogeny? - Kibeom Kim, Juseong Kim, Minwook Kim, Hyewon Lee, Giltae Song:
Therapeutic gene target prediction using novel deep hypergraph representation learning. - Tingpeng Yang, Yonghong He, Yu Wang:
Introducing TEC-LncMir for prediction of lncRNA-miRNA interactions through deep learning of RNA sequences. - Chelsea Chen Yuge, Ee Soon Hang, Madasamy Ravi Nadar Mamtha, Shashikant Vishwakarma, Sijia Wang, Cheng Wang, Nguyen Quoc Khanh Le:
RNA-ModX: a multilabel prediction and interpretation framework for RNA modifications. - Mingzhi Yuan, Ao Shen, Yingfan Ma, Jie Du, Bohan An, Manning Wang:
ProteinF3S: boosting enzyme function prediction by fusing protein sequence, structure, and surface. - Shunying Liu, Lingfei Li, Yi Liang, Yang Tan, Xiaoyu Wang, Yanhai Feng, Nian Chen, Xia Lei:
Novel genetic insight for psoriasis: integrative genome-wide analyses in 863 080 individuals and proteome-wide Mendelian randomization. - Md. Zubbair Malik, Mohammed Dashti, Amit Jangid, Arshad Channanath, Sumi Elsa John, R. K. Brojen Singh, Fahd Al-Mulla, Thangavel Alphonse Thanaraj:
Complex p53 dynamics regulated by miR-125b in cellular responses to reactive oxidative stress and DNA damage. - Ruogu Wang, Yunlong Feng, Alex M. Valm:
A framework of multi-view machine learning for biological spectral unmixing of fluorophores with overlapping excitation and emission spectra. - Zheng Su, Mingyan Fang, Andrei Smolnikov, Fatemeh Vafaee, Marcel E. Dinger, Emily C. Oates:
Post-transcriptional regulation supports the homeostatic expression of mature RNA. - Correction to: Synthetic plasma pool cohort correction for affinity-based proteomics datasets allows multiple study comparison.
- Yves Gaetan Nana Teukam, Federico Zipoli, Teodoro Laino, Emanuele Criscuolo, Francesca Grisoni, Matteo Manica:
Integrating genetic algorithms and language models for enhanced enzyme design. - Ankang Wei, Huanghan Zhan, Zhen Xiao, Weizhong Zhao, Xingpeng Jiang:
A novel framework for phage-host prediction via logical probability theory and network sparsification. - Yiru Pan, Xingyu Ji, Jiaqi You, Lu Li, Zhenping Liu, Xianlong Zhang, Zeyu Zhang, Maojun Wang:
CSGDN: contrastive signed graph diffusion network for predicting crop gene-phenotype associations. - Jing Li, Qinglin Mei, Chaoxia Yang, Naibo Zhu, Guojun Li:
TransBic: bucket trend-preserving biclustering for finding local and interpretable expression patterns. - Xiaotao Shen, Songjie Chen, Liang Liang, Monika Avina, Hanyah Zackriah, Laura Jelliffe-Pawlowski, Larry Rand, Michael P. Snyder:
Longitudinal urine metabolic profiling and gestational age prediction in human pregnancy. - Rui Niu, Jingwei Wang, Yanli Li, Jiren Zhou, Yang Guo, Xuequn Shang:
Attention-aware differential learning for predicting peptide-MHC class I binding and T cell receptor recognition. - Yushuang He, Feng Zhou, Jiaxing Bai, Yichun Gao, Xiaobing Huang, Ying Wang:
ViTax: adaptive hierarchical viral taxonomy classification with a taxonomy belief tree on a foundation model. - Dongping Liu, Dinghao Liu, Kewei Sheng, Zhenyong Cheng, Zixuan Liu, Yanling Qiao, Shangxuan Cai, Yulong Li, Jubo Wang, Hongyang Chen, Chi Hu, Peng Xu, Bin Di, Jun Liao:
STNGS: a deep scaffold learning-driven generation and screening framework for discovering potential novel psychoactive substances. - Qinglong Zhang, Liping Kang, Haoran Yang, Fei Liu, Xiaohui Wu:
Supervised analysis of alternative polyadenylation from single-cell and spatial transcriptomics data with spvAPA. - Arnaud Guille, José Adélaïde, Pascal Finetti, Fabrice André, Daniel Birnbaum, Emilie Mamessier, François Bertucci, Max Chaffanet:
A benchmarking study of individual somatic variant callers and voting-based ensembles for whole-exome sequencing. - Zhilong Liu, Hai Lin, Xiang Li, Hao Xue, Yuer Lu, Fei Xu, Jianwei Shuai:
The network structural entropy for single-cell RNA sequencing data during skin aging. - Yongjie Xu, Zelin Zang, Bozhen Hu, Yue Yuan, Cheng Tan, Jun Xia, Stan Z. Li:
Complex hierarchical structures analysis in single-cell data with Poincaré deep manifold transformation. - Dominik Lux, Katrin Marcus-Alic, Martin Eisenacher, Julian Uszkoreit:
ProtGraph: a tool for the quick and comprehensive exploration and exploitation of the peptide search space derived from protein sequence databases using graphs. - Ezechiel B. Tibiri, Palwende R. Boua, Issiaka Soulama, Christine Dubreuil-Tranchant, Ndomassi Tando, Charlotte Tollenaere, Christophe Brugidou, Romaric K. Nanema, Fidèle Tiendrebeogo:
Challenges and opportunities of developing bioinformatics platforms in Africa: the case of BurkinaBioinfo at Joseph Ki-Zerbo University, Burkina Faso. - Linjie Wang, Huixia Zhang, Bo Yi, Weidong Xie, Kun Yu, Wei Li, Keqin Li, Dazhe Zhao:
FactVAE: a factorized variational autoencoder for single-cell multi-omics data integration analysis. - Haoyang Cheng, Zhuoran Liang, Yijin Wu, Jiamin Hu, Bijin Cao, Zekun Liu, Bo Liu, Han Cheng, Ze-Xian Liu:
Inferring kinase-phosphosite regulation from phosphoproteome-enriched cancer multi-omics datasets. - Pengcheng Yang, Youngwoo Lee, Daniel B. Szymanski, Jun Xie:
Integrating CORUM and co-fractionation mass spectrometry to create enhanced benchmarks for protein complex predictions. - Chenrui Duan, Zelin Zang, Yongjie Xu, Hang He, Siyuan Li, Zihan Liu, Zhen Lei, Ju-Sheng Zheng, Stan Z. Li:
FGeneBERT: function-driven pre-trained gene language model for metagenomics. - Peng Xia, Wei Wu, Quanzhong Liu, Bin Huang, Min Wu, Zihan Lin, Mengyan Zhu, Miao Yu, Ying Qu, Kening Li, Lingxiang Wu, Ruohan Zhang, Qianghu Wang:
SCANER: robust and sensitive identification of malignant cells from the scRNA-seq profiled tumor ecosystem. - Junxi Xie, Xiaopeng Jin, Hang Wei, Saisai Sun, Yumeng Liu:
IDP-EDL: enhancing intrinsically disordered protein prediction by combining protein language model and ensemble deep learning. - Juho Pelto, Kari Auranen, Janne V. Kujala, Leo Lahti:
Elementary methods provide more replicable results in microbial differential abundance analysis. - Johanna Elena Schmitz, Sven Rahmann:
A comprehensive review and evaluation of species richness estimation. - Jiancheng Zhong, Zhiwei Zou, Jie Qiu, Shaokai Wang:
ScFold: a GNN-based model for efficient inverse folding of short-chain proteins via spatial reduction. - Luuk R. Hoegen Dijkhof, Teemu K. E. Rönkkö, Hans C. von Vegesack, Jacob Lenzing, Alexander S. Hauser:
Deep learning in GPCR drug discovery: benchmarking the path to accurate peptide binding. - Harvard Wai Hann Hui, Wei Xin Chan, Wilson Wen Bin Goh:
Assessing the impact of batch effect associated missing values on downstream analysis in high-throughput biomedical data. - Isaac Torres, Shufan Zhang, Amanda Bouffier, Michael Skaro, Yue Wu, Lauren Stupp, Jonathan P. Arnold, Y. Anny Chung, Heinz-Bernd Schüttler:
MINE: a new way to design genetics experiments for discovery. - Yizhen Wang, Li Cheng, Yanyun Zhang, Yujia Cao, Daniyal M. Al-Ghazzawi:
DEKP: a deep learning model for enzyme kinetic parameter prediction based on pretrained models and graph neural networks. - Luciano I Zablocki, Leandro A Bugnon, Matias Gerard, Leandro E. Di Persia, Georgina Stegmayer, Diego H. Milone:
Comprehensive benchmarking of large language models for RNA secondary structure prediction. - Andrea Lomagno, Ishak Yusuf, Gabriele Tosadori, Dario Bonanomi, Pietro Luigi Mauri, Dario Di Silvestre:
CoPPIs algorithm: a tool to unravel protein cooperative strategies in pathophysiological conditions. - Chen M. Chen, Rosemary Yu:
A multi-step completion process model of cell plasticity. - Gang Wen, Limin Li:
Federated transfer learning with differential privacy for multi-omics survival analysis. - Xinlong Wen, Hao Liu, Wenhan Long, Shuoying Wei, Rongbo Zhu:
Consistent semantic representation learning for out-of-distribution molecular property prediction. - Xinyi Mou, Haoyu Du, Guanghua Qiao, Jing Li:
Evaluation of imputation and imputation-free strategies for differential abundance analysis in metaproteomics data. - Guo-Hua Yuan, Jinzhe Li, Zejun Yang, Yao-Qi Chen, Zhonghang Yuan, Tao Chen, Wanli Ouyang, Nanqing Dong, Li Yang:
Deep generative model for protein subcellular localization prediction. - Jammi Prasanthi Sirasani, Cory Gardner, Gihwan Jung, Hyunju Lee, Tae-Hyuk Ahn:
Bioinformatic approaches to blood and tissue microbiome analyses: challenges and perspectives. - Gen Li, Sijie Yao, Long Fan:
Shared-weight graph framework for comprehensive protein stability prediction across diverse mutation types. - Fabio Cumbo, Simone Truglia, Emanuel Weitschek, Daniel Blankenberg:
Feature selection with vector-symbolic architectures: a case study on microbial profiles of shotgun metagenomic samples of colorectal cancer. - Tingyu Liu, Qiuhao Chen, Renjie Liu, Yuzhi Sun, Yadong Wang, Yan Zhu, Tianyi Zhao:
DMGAT: predicting ncRNA-drug resistance associations based on diffusion map and heterogeneous graph attention network. - Chunying Wang, Di Zhang, Yuexin Ma, Yonghao Zhao, Ping Liu, Xiang Li:
WheatGP, a genomic prediction method based on CNN and LSTM. - Yun Zuo, Xingze Fang, Jiankang Chen, Jiayi Ji, Yuwen Li, Zeyu Wu, Xiangrong Liu, Xiangxiang Zeng, Zhaohong Deng, Hongwei Yin, Anjing Zhao:
MlyPredCSED: based on extreme point deviation compensated clustering combined with cross-scale convolutional neural networks to predict multiple lysine sites in human. - Marek Nowicki, Magdalena Mroczek, Dhananjay Mukhedkar, Piotr Bala, Ville Nikolai Pimenoff, Laila Sara Arroyo Mühr:
HPV-KITE: sequence analysis software for rapid HPV genotype detection. - Jin Zhang, Yan Yang, Muheng Shang, Lei Guo, Daoqiang Zhang, Lei Du:
Mutual-assistance learning for trustworthy biomarker discovery and disease prediction. - Chun Shen Lim, Alexandra K. Gibbon, Anh Thu Tran Nguyen, Gabrielle S. W. Chieng, Chris M. Brown:
RIBOSS detects novel translational events by combining long- and short-read transcriptome and translatome profiling. - Zhijian Huang, Kai Chen, Xiaojun Xiao, Ziyu Fan, Yuanpeng Zhang, Lei Deng:
DeepHeteroCDA: circRNA-drug sensitivity associations prediction via multi-scale heterogeneous network and graph attention mechanism. - Ying Li, Qifeng Hu, Siyu Han, Rui Wang-Sattler, Wei Du:
Multi-Manifolds fusing hyperbolic graph network balanced by pareto optimization for identifying spatial domains of spatial transcriptomics. - Fengyue Zhang, Xuqi Zhao, Jinrui Wei, Lichuan Wu:
PathSynergy: a deep learning model for predicting drug synergy in liver cancer. - Cong M. Pham, Timothy J. Rankin, Timothy P. Stinear, Calum J. Walsh, Feargal J. Ryan:
TaxSEA: rapid interpretation of microbiome alterations using taxon set enrichment analysis and public databases. - Steffen Klamt, Jürgen Zanghellini, Axel von Kamp:
Minimal cut sets in metabolic networks: from conceptual foundations to applications in metabolic engineering and biomedicine. - Hongtao Yu, Guojing He, Wei Wang, Senbiao Qin, Yu Wang, Mingze Bai, Kunxian Shu, Dan Pu:
A graph neural network approach for accurate prediction of pathogenicity in multi-type variants. - Yutao Zhang, Haocheng Ding, Zhiguang Huo, Li Chen:
A novel Bayesian hierarchical model for detecting differential circadian pattern in transcriptomic applications. - Anqiang Ye, Ji-Yun Zhang, Qian Xu, Hai-Xia Guo, Zhen Liao, Hongtu Cui, Dongdong Zhang, Feng-Biao Guo:
Carmna: classification and regression models for nitrogenase activity based on a pretrained large protein language model. - Yi Zhang, Jindi Huang, Xinze Li, Wenqi Sun, Nana Zhang, Jiquan Zhang, Tiegen Chen, Ling Wang:
Self-awareness of retrosynthesis via chemically inspired contrastive learning for reinforced molecule generation. - Zeyin Li, Min Wang, Songge Li, Fangyuan Shi:
MIRACN: a residual convolutional neural network for predicting cell line specific functional regulatory variants. - Haicheng Li, Junhua Niu, Yalan Sheng, Yifan Liu, Shan Gao:
SMAC: identifying DNA N6-methyladenine (6mA) at the single-molecule level using SMRT CCS data. - Shuo Li, Pei Fen Kuan:
A systematic evaluation of cell-type-specific differential methylation analysis in bulk tissue. - Wengyu Zhang, Qi Tian, Yi Cao, Wenqi Fan, Dongmei Jiang, Yaowei Wang, Qing Li, Xiao-Yong Wei:
GraphATC: advancing multilevel and multi-label anatomical therapeutic chemical classification via atom-level graph learning. - Jinyu Chen, Wenwen Min:
sTPLS: identifying common and specific correlated patterns under multiple biological conditions. - Dao Tran, Ha Nguyen, Van-Dung Pham, Phuong Nguyen, Hung Nguyen Luu, Liem Minh Phan, Christin Blair Destefano, Sai-Ching Jim Yeung, Tin Nguyen:
A comprehensive review of cancer survival prediction using multi-omics integration and clinical variables. - Yuxuan Pang, Chunxuan Wang, Yao-zhong Zhang, Zhuo Wang, Seiya Imoto, Tzong-Yi Lee:
STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics. - Shengjie Liu, Tianwei Yu:
Nonlinear embedding and integration of omics data: a fast and tuning-free approach.
Volume 26, Number 3, 2025
- Jing Yang, Minggui Song, Yifan Bu, Haonan Zhao, Chenghui Liu, Ting Zhang, Chujun Zhang, Shutu Xu, Chuang Ma:
Machine learning-augmented m6A-Seq analysis without a reference genome. - Zhiwei Cheng, Yongyong Ren, Xinbo Wang, Yuening Zhang, Yingqi Hua, Hongyu Zhao, Hui Lu:
A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics. - Kaizhuang Jing, Tingchu Wei, Xuedie Gu, Guoliang Lin, Lin Liu, Jing Luo:
Deep learning reveals determinants of transcriptional infidelity at nucleotide resolution in the allopolyploid line by goldfish and common carp hybrids. - Xuchao Zhang, Jing Chen, Yongtian Wang, Xiaofeng Wang, Jialu Hu, Jiajie Peng, Xuequn Shang, Yanpu Wang, Tao Wang:
cfMethylPre: deep transfer learning enhances cancer detection based on circulating cell-free DNA methylation profiling. - Jiahui Guan, Lantian Yao, Peilin Xie, Zhihao Zhao, Dian Meng, Tzong-Yi Lee, Junwen Wang, Ying-Chih Chiang:
Graph-RPI: predicting RNA-protein interactions via graph autoencoder and self-supervised learning strategies. - Yuxin Lin, Zongming Jia, Jixiang Wu, Hubo Yang, Xin Chen, He Wang, Xuedong Wei, Wenying Yan, Xin Qi, Yuhua Huang:
Knowledge-guided multi-level network modeling with experimental characterization identifies PRKCA as a novel biomarker and tumor suppressor triggering ferroptosis in prostate cancer. - Xianjun Han, Zhenglong Zhang, Can Bai, Zijian Wu:
Integrated multimodal hierarchical fusion and meta-learning for enhanced molecular property prediction. - Su Xu, Duan Chen, Xue Wang, Shaoyu Li:
Robustness and resilience of computational deconvolution methods for bulk RNA sequencing data. - Hong-Qi Zhang, Xin-Ran Lin, Yan-Ting Wang, Wen-Fang Pei, Guang-Ji Ma, Ze-Xu Zhou, Ke-Jun Deng, Dan Yan, Tian-Yuan Liu:
EDS-Kcr: deep supervision based on large language model for identifying protein lysine crotonylation sites across multiple species. - Guliang Wang, Ioannis Mouratidis, Kimonas Provatas, Nikol Chantzi, Michail Patsakis, Ilias Georgakopoulos-Soares, Karen M. Vasquez:
ZSeeker: an optimized algorithm for Z-DNA detection in genomic sequences. - Tae Hyun Kim, Harim Kim, Hyunjin Hwang, Shinwhan Kang, Kijung Shin, Inwha Baek:
Gene expression inference based on graph neural networks using L1000 data. - Tung Dang, Yushiro Fuji, Kie Kumaishi, Erika Usui, Shungo Kobori, Takumi Sato, Megumi Narukawa, Yusuke Toda, Kengo Sakurai, Yuji Yamasaki, Hisashi Tsujimoto, Masami Yokota Hirai, Yasunori Ichihashi, Hiroyoshi Iwata:
I-SVVS: integrative stochastic variational variable selection to explore joint patterns of multi-omics microbiome data. - Pi-Jing Wei, Huaiwan Jin, Zhen Gao, Yansen Su, Chun-Hou Zheng:
GAEDGRN: reconstruction of gene regulatory networks based on gravity-inspired graph autoencoders. - Yuhuan Liu, Xueying Wang, Haitian Zhong, Jixiu Zhai, Xiaojuan Gong, Tianchi Lu:
PhosF3C: a feature fusion architecture with fine-tuned protein language model and conformer for prediction of general phosphorylation site. - Jianwei Huang, Youli Zhang, Shulin Ren, Ziyang Wang, Xiaocheng Jin, Xiaoli Lu, Yu Zhang, Xiaoping Min, Shengxiang Ge, Jun Zhang, Ningshao Xia:
MambaPhase: deep learning for liquid-liquid phase separation protein classification. - Alex McSweeney-Davis, Chengran Fang, Emmanuel Caruyer, Anne Kerbrat, Jing-Rebecca Li:
Alpha_Mesh_Swc: automatic and robust surface mesh generation from the skeleton description of brain cells. - Suresh Pokharel, Kepha Barasa, Pawel Pratyush, Dukka B. KC:
PLM-DBPs: enhancing plant DNA-binding protein prediction by integrating sequence-based and structure-aware protein language models. - Mikhail S. Gelfand:
On "Bioinformatics in Russia: history and present-day landscape" by M.A. Nawaz, I.E. Pamirsky, and K.S. Golokhvast. - Muhammad A Nawaz, Igor E. Pamirsky, Kirill S. Golokhvast:
Response to letter to editor "On 'Bioinformatics in Russia: history and present-day landscape' by M.A. Nawaz, I.E. Pamirsky, and K.S. Golokhvast" by Mikhail Gelfand. - Kun Wu, Zixu Wang, Xiulong Yang, Yangyang Chen, Fulvio Mastrogiovanni, Jialu Zhang, Lizhuang Liu:
TransMA: an explainable multi-modal deep learning model for predicting properties of ionizable lipid nanoparticles in mRNA delivery. - Jing Li, Jia Mi, Wei Lin, Fengjuan Tian, Jing Wan, Jingyang Gao, Yigang Tong:
VirNucPro: an identifier for the identification of viral short sequences using six-frame translation and large language models. - Jingjing Wang, Yanpeng Zhao, Zhijiang Yang, Ge Yao, Penggang Han, Jiajia Liu, Chang Chen, Peng Zan, Xiukun Wan, Xiaochen Bo, Hui Jiang:
IECata: interpretable bilinear attention network and evidential deep learning improve the catalytic efficiency prediction of enzymes. - Yijie He, Yaqin Tang, Pengcheng Tan, Dongyu Huang, Yongheng Wang, Tong Wen, Lin Huang, Jia Wang, Lizhen Shao, Qinyu Cai, Zhimou Li, Yueyang Wang, Taihang Liu, Zhijie Han:
Genetic regulation of lncRNA expression in whole human brain and their contribution to CNS disorders. - Keisuke Yamada, Kanta Suga, Naoko Abe, Koji Hashimoto, Susumu Tsutsumi, Masahito Inagaki, Fumitaka Hashiya, Hiroshi Abe, Michiaki Hamada:
Multi-objective computational optimization of human 5′ UTR sequences. - Maren Hackenberg, Laia Canal Guitart, Rolf Backofen, Harald Binder:
Evaluating discrepancies in dimensionality reduction for time-series single-cell RNA-sequencing data. - Alvira Ajadee, Sabkat Mahmud, Md. Ahad Ali, Md. Manir Hossain Mollah, Reaz Ahmmed, Md. Nurul Haque Mollah:
In-silico discovery of type-2 diabetes-causing host key genes that are associated with the complexity of monkeypox and repurposing common drugs. - Peidong Zhang, Xingang Peng, Rong Han, Ting Chen, Jianzhu Ma:
Rag2Mol: structure-based drug design based on retrieval augmented generation. - Chen Chen, Yong Xu, Jian Ouyang, Xiangyi Xiong, Pawel P. Labaj, Agnieszka Chmielarczyk, Anna Rózanska, Hao Zhang, Keyang Liu, Tieliu Shi, Jun Wu:
VirulentHunter: deep learning-based virulence factor predictor illuminates pathogenicity in diverse microbial contexts. - Mingxuan Zhang, Yinglei Lai:
An order-preserving batch-effect correction method based on a monotonic deep learning framework. - Yu Cheng, Xinjia Ruan, Xiaofan Lu, Yuqing Yang, Yuhang Wang, Shangjin Yan, Yuzhe Sun, Fangrong Yan, Liyun Jiang, Tiantian Liu:
Accounting for the impact of rare variants on causal inference with RARE: a novel multivariable Mendelian randomization method. - Osafu Augustine Egbon, John W. Hickey, Benedict Anchang:
Fusion of spatiotemporal and network models to prioritize multiscale effects in single-cell perturbations. - Correction to: Bioinformatics in Russia: history and present-day landscape.
- Yihe Yang, Noah Lorincz-Comi, Mengxuan Li, Xiaofeng Zhu:
A multivariable cis-Mendelian randomization method robust to weak instrument bias and horizontal pleiotropy bias. - Alain J. Mbebi, Facundo Mercado, David Hobby, Hao Tong, Zoran Nikoloski:
Advances in multi-trait genomic prediction approaches: classification, comparative analysis, and perspectives. - Cheng Zhu, Sen Cao, Tianfeng Shang, Jingjing Guo, An Su, Chengxi Li, Hongliang Duan:
Predicting the structures of cyclic peptides containing unnatural amino acids by HighFold2. - Hailong Yang, Jia Wang, Wenyan Wang, Shufang Shi, Lijing Liu, Yuhua Yao, Geng Tian, Peizhen Wang, Jialiang Yang:
MMsurv: a multimodal multi-instance multi-cancer survival prediction model integrating pathological images, clinical information, and sequencing data. - Xiaoyan Yu, Yixuan Ren, Min Xia, Zhenqiu Shu, Liehuang Zhu:
Decoupled GNNs based on multi-view contrastive learning for scRNA-seq data clustering. - Mike van Santvoort, Federica Eduati:
An algorithmic perspective on deciphering cell-cell interactions with spatial omics data. - Xichen Liao, Qi Liu, Guohui Chuai:
PrimeNet: rational design of Prime editing pegRNAs by deep learning. - Xin Li, Fan Yang, Yibo Zhang, Zijian Yang, Ruanqi Chen, Meng Zhou, Lin Yang:
DeepTFtyper: an interpretable morphology-aware graph neural network for translating histopathology images into molecular subtypes in small cell lung cancer. - Feifei Xia, Max A. Verbiest, Oxana Lundström, Tugce Bilgin Sonay, Michael Baudis, Maria Anisimova:
Multicancer analyses of short tandem repeat variations reveal shared gene regulatory mechanisms. - Xudong Liu, Zhiwei Nie, Haorui Si, Xurui Shen, Yutian Liu, Xiansong Huang, Tianyi Dong, Fan Xu, Zhixiang Ren, Peng Zhou, Jie Chen:
Generative prediction of real-world prevalent SARS-CoV-2 mutation with in silico virus evolution. - Xun Wang, Tongyu Han, Runqiu Feng, Zhijun Xia, Hanyu Wang, Wenqian Yu, Huanhuan Dai, Haonan Song, Tao Song:
GTE-PPIS: a protein-protein interaction site predictor based on graph transformer and equivariant graph neural network. - Liye Chen, Biaoshun Li, Yihao Chen, Mujie Lin, Shipeng Zhang, Chenxin Li, Yu Pang, Ling Wang:
ADCNet: a unified framework for predicting the activity of antibody-drug conjugates. - Bingying Luo, Fei Teng, Guo Tang, Weixuan Cen, Xing Liu, Jinmiao Chen, Chi Qu, Xuanzhu Liu, Xin Liu, Wenyan Jiang, Huaqiang Huang, Yu Feng, Xue Zhang, Min Jian, Mei Li, Feng Xi, Guibo Li, Sha Liao, Ao Chen, Weimiao Yu, Xun Xu, Jiajun Zhang:
StereoMM: a graph fusion model for integrating spatial transcriptomic data and pathological images. - Sara H. Mohamed, Mohamed Hamed, Hussain A Alamoudi, Zayd Jastaniah, Fadhl M. Al-Akwaa, Asmaa Reda:
Multi-omics analysis of Helicobacter pylori-associated gastric cancer identifies hub genes as a novel therapeutic biomarker. - Yu Shi, Wei Xu, Pingzhao Hu:
Out of distribution learning in bioinformatics: advancements and challenges. - Zequn Zhang, Huijun Li, Yuxi Chen, Xiaoli Li, Dongqing Wei, Hongyan Wu:
HGCMLDA: predicting lncRNA-disease associations using hypergraph contrastive learning and multi-scale attentional feature fusion. - Maider Aguerralde-Martin, Mónica Clemente-Císcar, Ana Conesa, Sonia Tarazona:
MORE interpretable multi-omic regulatory networks to characterise phenotypes. - Xianglin Zhang, Wei Zhang, Jinyi Zhang, Xiuhong Lyu, Haoran Pan, Tianwei Jia, Ting Wang, Xiaowo Wang, Haiyang Guo:
Simulation-guided pan-cancer analysis identifies a novel regulator of CpG island hypermethylation heterogeneity. - Kanglin Hsieh, Kai Zhang, Yan Chu, Lishan Yu, Xiaoyang Li, Nuo Hu, Isha Kawosa, Patrick G. Pilié, Pratip K. Bhattacharya, Degui Zhi, Xiaoqian Jiang, Zhongming Zhao, Yulin Dai:
iGTP: learning interpretable cellular embedding for inferring biological mechanisms underlying single-cell transcriptomics. - Editor's Note on 'Bioinformatics in Russia: history and present-day landscape'.
- Shangwei Guo, Shengming Zhou, Guohua Wang, Fang Wang:
SCPline: An interactive framework for the single-cell proteomics data preprocessing. - Tianhao Li, Zixuan Wang, Yuhang Liu, Sihan He, Quan Zou, Yongqing Zhang:
An overview of computational methods in single-cell transcriptomic cell type annotation. - Jun Hu, Yu Zhou, Wen-Yi Zhang, Xiao-Gen Zhou:
RLEAAI: improving antibody-antigen interaction prediction using protein language model and sequence order information. - Anas Bilal, Muhammad Taseer Suleman, Khalid Almohammadi, Abdulkareem Alzahrani, Xiaowen Liu:
2OM-Pred: prediction of 2-O-methylation sites in ribonucleic acid using diverse classifiers. - Liangcan Li, Xin Li, Hao Wu:
A novel deep learning framework with dynamic tokenization for identifying chromatin interactions along with motif importance investigation. - Jing Wang, Junfeng Xia, Dayu Tan, Yunjie Ma, Yansen Su, Chun-Hou Zheng:
Multi-view clustering for single-cell RNA-seq data based on graph fusion. - Giulia Cesaro, James Shiniti Nagai, Nicolò Gnoato, Alice Chiodi, Gaia Tussardi, Vanessa Klöker, Carmelo Vittorio Musumarra, Ettore Mosca, Ivan G. Costa, Barbara Di Camillo, Enrica Calura, Giacomo Baruzzo:
Advances and challenges in cell-cell communication inference: a comprehensive review of tools, resources, and future directions. - Rym Bouriga, Caroline Bailleux, Jocelyn Gal, Emmanuel Chamorey, Baharia Mograbi, Jean-Michel Hannoun-Levi, Gérard Milano:
Advances and critical aspects in cancer treatment development using digital twins. - Zhixia Teng, Zhaowen Tian, Murong Zhou, Guohua Wang, Zhen Tian, Yuming Zhao:
Enhancing LncRNA-miRNA interaction prediction with multimodal contrastive representation learning. - Correction to: ScInfeR: an efficient method for annotating cell types and sub-types in single-cell RNA-seq, ATAC-seq, and spatial omics.
- Yuting Hu, Feng Hu, Hongwen Zhang, Hongling Xu, Jixiang Gao, Wenshuai Deng, Zijing Tian, Qiaoyu Hu, Honglin Li, Yanyan Diao:
RPSubAlign: a novel sequence-based molecular representation method for retrosynthesis prediction with improved validity and robustness. - Murong Zhou, Zeyu Luo, Yu-Hang Yin, Qiaoming Liu, Guohua Wang, Yuming Zhao:
scATD: a high-throughput and interpretable framework for single-cell cancer drug resistance prediction and biomarker identification. - Jelard Aquino, Daniel Witoslawski, Steve Park, Jessica Holder, Amei Amei, Mira V. Han:
A novel splicing graph allows a direct comparison between exon-based and splice junction-based approaches to alternative splicing detection. - Fulan Deng, Jiawei Zou, Miaochen Wang, Yida Gu, Jiale Wu, Lianchong Gao, Yuan Ji, Henry H. Y. Tong, Jie Chen, Wantao Chen, Lianjiang Tan, Yaoqing Chu, Xin Zou, Jie Hao:
DECEPTICON: a correlation-based strategy for RNA-seq deconvolution inspired by a variation of the Anna Karenina principle. - Sriniketh Vangaru, Debswapna Bhattacharya:
To pack or not to pack: revisiting protein side-chain packing in the post-AlphaFold era. - Chen Yang, Yingqi Zhao, Boyuan Xue, Shaojie Wang, Haijia Su:
PYF: a multi-functional algorithm for predicting production and optimizing metabolic engineering strategy in Escherichia coli microbial consortia. - Saiyam Jogani, Anand Santosh Pol, Mayur Prajapati, Amit Samal, Kriti Bhatia, Jayendra Parmar, Urvik Patel, Falak Shah, Nisarg Vyas, Saurabh Gupta:
scaLR: a low-resource deep neural network-based platform for single cell analysis and biomarker discovery. - Jingchen Zhai, Xiguang Qi, Lianjin Cai, Yue Liu, Haocheng Tang, Lei Xie, Junmei Wang:
NNKcat: deep neural network to predict catalytic constants (Kcat) by integrating protein sequence and substrate structure with enhanced data imbalance handling. - Fei Ye, Mao Chen, Yixuan Huang, Ruihao Zhang, Xuqi Li, Xiuyuan Wang, Sanyang Han, Lan Ma, Xiao Liu:
LightCTL: lightweight contrastive TCR-pMHC specificity learning with context-aware prompt. - Partha Pratim Ray:
Should LLMs be over empowered for high-stake regulatory research? - Asish Kumar Swain, Rajveer Singh Shekhawat, Pankaj Yadav:
ScInfeR: an efficient method for annotating cell types and sub-types in single-cell RNA-seq, ATAC-seq, and spatial omics. - Li Huang, Weikang Gong, Dongsheng Chen:
scValue: value-based subsampling of large-scale single-cell transcriptomic data for machine and deep learning tasks. - Li-Mei Qian, Shi-Xiang Wang, Wen Zhou, Zi-Xin Qin, Ying-Nan Wang, Qi Zhao, Rui-Hua Xu:
Individualized metagenomic network model for colorectal cancer diagnosis: insights into viral regulation of gut microecology. - Xinyi Tang, Ran Liu:
De-motif sampling: an approach to decompose hierarchical motifs with applications in T cell recognition. - Hongyu Zhang, Weining Li, Jinting Guan:
scTsI: an effective two-stage imputation method for single-cell RNA-seq data. - Yan Zhao, Huaiyu Wang:
Artificial intelligence-driven circRNA vaccine development: multimodal collaborative optimization and a new paradigm for biomedical applications. - Hao Mei, Zhiyuan Wang, Hang Yang, Xiaoke Li, Yaqing Xu:
Network analysis of multivariate time series data in biological systems: methods and applications. - Ting Li, Henghui Fan, Jianping Zhao, Xiaomei Yang, Junfeng Xia:
MultiPep-DLCL: recognition of multifunctional therapeutic peptides through deep learning with label-sequence contrastive learning. - Sina Majidian, Stephen Hwang, Mohsen Zakeri, Ben Langmead:
EvANI benchmarking workflow for evolutionary distance estimation. - Hongqiang Lyu, Pei Cao, Wenyao Long, Xiaoran Yin, Shengjun Xu, Laiyi Fu:
DeepExDC interprets genomic compartmentalization changes in single-cell Hi-C data. - Xin Gao, Hanqun Cao, Jinpeng Li, Jiezhong Qiu, Guangyong Chen, Pheng-Ann Heng:
Gated-GPS: enhancing protein-protein interaction site prediction with scalable learning and imbalance-aware optimization. - Yangyang Wang, Xinyu Yue, Shenghan Lou, Peinan Feng, Binbin Cui, Yanlong Liu:
Gene Swin transformer: new deep learning method for colorectal cancer prognosis using transcriptomic data. - Ning Wang, Minghui Wu, Wenchao Gu, Chenglong Dai, Zongru Shao, K. P. Subbalakshmi:
MSFT-transformer: a multistage fusion tabular transformer for disease prediction using metagenomic data. - Rhys Gillman, Matt A. Field, Ulf Schmitz, Lionel Hebbard:
TARGET-SL: precision essential gene prediction using driver prioritisation and synthetic lethality. - Zehua Sun, Jing Xu, Yumeng Zhang, Yiwen Zhang, Zhikang Wang, Xiaoyu Wang, Shanshan Li, Yuming Guo, Hsin Hui Shen, Jiangning Song:
Multimodal geometric learning for antimicrobial peptide identification by leveraging alphafold2-predicted structures and surface features. - Ana Stolnicu, Nensi Ikonomi, Peter Eckhardt-Bellmann, Johann M. Kraus, Hans A. Kestler:
Robust signalling entropy estimation for biological process characterisation. - Runtian Gao, Heng Hu, Zhongjun Jiang, Shuqi Cao, Guohua Wang, Yuming Zhao, Tao Jiang:
SVHunter: long-read-based structural variation detection through the transformer model. - Mingjuan Wang, Xuetong Chen, Mingxing Liu, Huiying Luo, Shuangshuang Zhang, Jie Guo, Jinghui Wang, Li Zhou, Na Zhang, Hongyan Li, Chao Wang, Liang Li, Zhenzhong Wang, Haiqing Wang, Zihu Guo, Yan Li, Yonghua Wang:
Decoding herbal combination models through systematic strategies: insights from target information and traditional Chinese medicine clinical theory. - Rui Zhang, Huaming Wu:
GC-balanced polar codes correcting insertions, deletions and substitutions for DNA storage. - Zhiyue Tom Hu, Yaodong Yu, Ruoqiao Chen, Shan-Ju Yeh, Bin Chen, Haiyan Huang:
Large-scale information retrieval and correction of noisy pharmacogenomic datasets through residual thresholded deep matrix factorization. - Fangyu Mo, Qinghong Qian, Xiaolin Lu, Dihuai Zheng, Wenjie Cai, Jie Yao, Hongyu Chen, Yujie Huang, Xiang Zhang, Sanling Wu, Yifei Shen, Yinqi Bai, Yongcheng Wang, Weiqin Jiang, Longjiang Fan:
mKmer: an unbiased K-mer embedding of microbiomic single-microbe RNA sequencing data. - Sunghong Park, Dong-Gi Lee, Juhyeon Kim, Seung Ho Kim, Hyeon Jin Hwang, Hyunjung Shin, Hyun Goo Woo:
PPIxGPN: plasma proteomic profiling of neurodegenerative biomarkers with protein-protein interaction-based eXplainable graph propagational network. - Xiao Ding, Yun Ma, Shicheng Li, Jingze Liu, Luyao Qin, Aiping Wu:
Influenza virus reassortment patterns exhibit preference and continuity while uncovering cross-species transmission events. - Wenbo Guo, Zeyu Chen, Jin Gu:
Computational modeling of single-cell dynamics data. - Yuehua Ou, Qiyi Chen, Ningyu Zhong, Zhihua Du:
ProtPhage: a deep learning framework for phage viral protein identification and functional annotation. - Himansu Kumar, Zikang Chen, Abayomi Adegunlehin, Loren Trowbridge, Leonardo Aguilar, Pora Kim:
KinaseFusionDB: an integrative knowledge of kinase fusion proteins in multi-scales. - Xiang Lian, Xia Kuang, Dong-Dong Zhang, Qian Xu, Anqiang Ye, Cheng-Yu Wang, Hong-Tu Cui, Hai-Xia Guo, Ji-Yun Zhang, Yuan Liu, Ge-Fei Hao, Zhenshun Cheng, Feng-Biao Guo:
Systematic identification of cancer-type-specific drugs based on essential genes and validations in lung adenocarcinoma. - Ruilin Su, Binyang Huang, Junyan Tan, Zhencai Shen, Ping Zhong, Jianfeng Liu:
Mutual information stacking method for prediction of the growth traits in pigs. - Lauren Theunissen, Thomas Mortier, Yvan Saeys, Willem Waegeman:
Evaluation of out-of-distribution detection methods for data shifts in single-cell transcriptomics. - Lili Liu, Haixiang Zhang, Yinan Zheng, Tao Gao, Cheng Zheng, Kai Zhang, Lifang Hou, Lei Liu:
High-dimensional mediation analysis for longitudinal mediators and survival outcomes. - Tianjiao Zhang, Saihong Shao, Hongfei Zhang, Zhongqian Zhao, Xingjie Zhao, Zhao-Xiang Zhang, Zhenxing Wang, Guohua Wang:
KansformerEPI: a deep learning framework integrating KAN and transformer for predicting enhancer-promoter interactions.
Volume 26, Number 4, 2025
- Thomas Bikias, Evangelos Stamkopoulos, Sai T. Reddy:
PLMFit: benchmarking transfer learning with protein language models for protein engineering. - Richard A. Schäfer, Rendong Yang:
A comprehensive benchmark of tools for efficient genomic interval querying. - Chenyu Liu, Qianyi Lu, Jian Li, Di Wang, Zhuoru Wang, Wenli Chen, Yakun Zhang, Caiyu Zhang, Yue Gao, Shangwei Ning:
Dynamic changes of synergy relationship between lncRNA and immune checkpoint in cancer progression. - Xinyue Cui, Lingyu Ge, Xia Chen, Zexin Lv, Suhui Wang, Xiaogen Zhou, Guijun Zhang:
Beyond static structures: protein dynamic conformations modeling in the post-AlphaFold era. - Yajunzi Wang, Jing Li, Haoruo Zha, Shuhe Liu, Daiyun Huang, Lei Fu, Xin Liu:
Paradigms, innovations, and biological applications of RNA velocity: a comprehensive review. - Daehun Bae, Minsang Kim, Jiwon Seo, Hojung Nam:
AI-guided discovery and optimization of antimicrobial peptides through species-aware language model. - Yue Yang, Kairui Guo, Yonggang Zhang, Zhen Fang, Hua Lin, Mark Grosser, Deon Venter, Weihai Lu, Mengjia Wu, Dennis Cordato, Guangquan Zhang, Jie Lu:
MetaGeno: a chromosome-wise multi-task genomic framework for ischaemic stroke risk prediction. - Phi Le, Leah Ung, Hai Yang, Anwen Huang, Tao He, Peter Bruno, David Y. Oh, Bridget P. Keenan, Li Zhang:
PepTCR-Net: prediction of multi-class antigen peptides by T-cell receptor sequences with deep learning. - Yan Sun, Yan Zhao, Junliang Shang, Baojuan Qin, Xiaohan Zhang, Jin-Xing Liu:
scRDAN: a robust domain adaptation network for cell type annotation across single-cell RNA sequencing data. - Keichin N. G:
Ensemble learning methods and heterogeneous graph network fusion: building drug-gene-disease triple association prediction models. - Catalina Gonzalez Gomez, Manuel Rosa-Calatrava, Julien Fouret:
Reconciling multiple connectivity-based systems biology methods for drug repurposing. - Anjie Qiao, Yuting Chen, Junjie Xie, Weifeng Huang, Hao Zhang, Qirui Deng, Jiahua Rao, Ji Deng, Fanbo Meng, Zhen Wang, Mingyuan Xu, Hongming Chen, Jiancong Xie, Shuangjia Zheng, Yuedong Yang, Guo-Bo Li, Jinping Lei:
A 3D pocket-aware lead optimization model with knowledge guidance and its application for discovery of new glutaminyl cyclase inhibitors. - Yijing Zhang, Shaobo Kang, Renjie Dou, Wanmei Zhang, Yuanyuan Liu, Yang Wu, Dongxue Li, Fangfang Fan, Yanyan Ping:
IMOP-Cancer: identifying mutation order pairs impacting cancer phenotypes. - Kuang-Cheng Hsu, Pei-Hua Wang, Bo-Han Su, Yufeng Jane Tseng:
A robust and interpretable graph neural network-based protocol for predicting p-glycoprotein substrates. - Bishal Shrestha, Zheng Wang:
HiC4D-SPOT: a spatiotemporal outlier detection tool for Hi-C data. - Si Chun Gu, Thomas Welton, Qiaoyang Sun, Yun-Cheng Wu, Eng King Tan, Zhi Dong Zhou:
The integration of genome-wide and transcriptome-wide association studies in neurodegenerative diseases: opportunities, challenges, and current methodological innovations. - Qi Zhao, Ze Li, Qian Mao, Tingwei Chen, Yiran Zhang, Bingle Li, Zheng Zhao, Xiaoya Fan:
MambaCpG: an accurate model for single-cell DNA methylation status imputation using mamba. - Yushu Shi, Liangliang Zhang, Kim-Anh Do, Robert R. Jenq, Christine B. Peterson:
CAT: a conditional association test for microbiome data using a permutation approach. - Ahmed Debit, Christophe Poulet, Claire Josse, Guy Jerusalem, Chloé-Agathe Azencott, Vincent Bours, Kristel Van Steen:
Assessing Random Forest self-reproducibility for optimal short biomarker signature discovery. - Qirui Zhou, Chaowen Li, Chao Chen, Songqing Gu, Weijun Sun, Zongmeng Zhang, Yishan Cai, Yonghui Huang, Hongtao Liu, Chao Yang, Xin Chen:
Path-MGCN: a pathway activity-based multi-view graph convolutional network for determining spatial domains. - Shanyang Ding, Dongjiang Niu, Xiaofeng Wang, Zhixin Zhang, Qunhao Zhang, Jun Xiao, Zhen Li:
MAPTrans: mutual attention transformer with dynamic meta-path pruning for drug repositioning. - Simone Rancati, Giovanna Nicora, Laura Bergomi, Tommaso Mario Buonocore, Daniel M. Czyz, Enea Parimbelli, Riccardo Bellazzi, Marco Salemi, Mattia Prosperi, Simone Marini:
SARITA: a large language model for generating the S1 subunit of the SARS-CoV-2 spike protein. - Xue Liu, Jianbin Kong, Yongtao Shan, Ziyue Yang, Jiafan Miao, Yuanfei Pan, Tianyang Luo, Zhiyuan Shi, Yingmei Wang, Qinyu Gou, Chunhui Yang, Hanzong Li, Chunmei Li, Shaochuan Li, Xu Zhang, Yanni Sun, Edward C. Holmes, Deyin Guo, Mang Shi:
SegFinder: an automated tool for identifying complete RNA virus genome segments through co-occurrence in multiple sequenced samples. - Yijun Mao, Xingcheng Peng, Jian Weng, Rongjin Jiang, Yingjie Kuang, Jiasi Weng, Rui Pang, Yunyan Xiong, Wanrong Gu, Deyu Tang:
MDNN: memetic deep neural network for genomic prediction. - Yingzhuo Wu, Jialuo Xu, Junming Li, Jia Gu, Xuequn Shang, Xingyi Li:
Deep graph convolutional network-based multi-omics integration for cancer driver gene identification. - Samantha L. Van Buren, C. Titus Brown, Tomasz Szmatola, Carrie J. Finno:
A comparative review of short genetic variant databases across humans and animal species. - Maribel Pérez-Ribera, Muhammad Faizan-Khan, Roger Giné, Josep M. Badia, Alexandra Junza, Oscar Yanes, Marta Sales-Pardo, Roger Guimerà:
SingleFrag: a deep learning tool for MS/MS fragment and spectral prediction and metabolite annotation. - Bharath Reddy Boya, Jin-Hyung Lee, Jae-Mun Choi, Jintae Lee:
Impact of halogenation on scaffold toxicity assessed using HD-GEM machine learning model. - Manuel Tognon, Alisa Kumbara, Andrea Betti, Lorenzo Ruggeri, Rosalba Giugno:
Benchmarking transcription factor binding site prediction models: a comparative analysis on synthetic and biological data. - Junliang Zhou, Ningji Gong, Yanjun Hu, Hong Yu, Guoyin Wang, Hao Wu:
GRANet: a graph residual attention network for gene regulatory network inference. - Max Ward, Mary Richardson, Mihir Metkar:
mRNA folding algorithms for structure and codon optimization. - Sunghong Park, Doyoon Kim, Ji-Hye Choi, Changhyung Hong, Sang Joon Son, Hyunwoong Roh, Hyunjung Shin, Hyun Goo Woo:
NeuroFANN: identification of neuropathological subtypes in dementia with plasma proteins by using functionally annotated neural network. - Xiaomei Li, Alex Whan, Meredith McNeil, David Starns, Jessica Irons, Samuel C. Andrew, Rad Suchecki:
A conceptual framework for human-AI collaborative genome annotation. - Yixiang Huang, Hao Jiang, Wai-Ki Ching, Dong Shen:
scRECL: representative ensembles with contrastive learning for scRNA-seq data clustering analysis. - Zhi Zhang, Qiucheng Sun, Chunyan Wang, Songrun Jiang:
scGGC: a two-stage strategy for single-cell clustering through cellular gene pathway construction. - Wei Zhang, Bowen Shao, Wenrui Li, Wenbo Guo, Jiaxin Lyu, Guangyi Chen, Chuanyuan Wang, Zhi-Ping Liu:
Inferring cell-type-specific gene regulatory network from cellular transcriptomics data with GeneLink+. - Ruochi Zhang, Haoran Wu, Chang Liu, Qian Yang, Yuting Xiu, Kewei Li, Ningning Chen, Yu Wang, Yan Wang, Xin Gao, Fengfeng Zhou:
PepLand: a large-scale pre-trained peptide representation model for a comprehensive landscape of both canonical and non-canonical amino acids. - Hua Shi, Zhouying Li, Quan Zou, Hui Yang:
Research on RNA modification in disease diagnosis and prognostic biomarkers: current status and challenges. - Fenglan Pang, Guangfu Xue, Wenyi Yang, Yideng Cai, Jinhao Que, Haoxiu Sun, Pingping Wang, Shuaiyu Su, Xiyun Jin, Qian Ding, Zuxiang Wang, Meng Luo, Yuexin Yang, Yi Lin, Renjie Tan, Yusong Liu, Zhaochun Xu, Qinghua Jiang:
TriCLFF: a multi-modal feature fusion framework using contrastive learning for spatial domain identification. - Pei Liu, Xiao Liang, Yue Li, Jiawei Luo:
ConvNTC: convolutional neural tensor completion for detecting "A-A-B" type biological triplets. - Yueyue Wang, Pengrui Teng, Zheyu Wu, Yuna Zhang, Zhisen Shen, Qinhu Zhang, De-Shuang Huang:
RGCN-BA: relational graph convolutional network with batch awareness for single-cell RNA sequencing clustering. - Xuechen Mu, Long Xu, Zhenyu Huang, Jing Yan, Bocheng Shi, Yishi Wang, Binyue Liu, Kai Zhang, Ying Xu:
BloodProST: prediction of blood-secretory proteins through self-training. - Wanshan Ning, Feibo Qin, Ziwei Zhou, Hang Yang, Chentan Li, Yaping Guo:
HybridKla: a hybrid deep learning framework for lactylation site prediction. - Laiyi Fu, Yangyi Zhou, Hongqiang Lyu, Hequan Sun:
Dual balanced augmented topological noncoding RNA disease triplet association in heterogeneous graphs. - Zhiwei Nie, Yiming Ma, Yutian Liu, Xiansong Huang, Zhihong Liu, Peng Yang, Fan Xu, Feng Yin, Zigang Li, Jie Fu, Zhixiang Ren, Wen-Bin Zhang, Jie Chen:
Predicting protein stability changes upon mutations with dual-view ensemble learning from single sequence. - Ana R. Baião, Zhaoxiang Cai, Rebecca C. Poulos, Phillip J. Robinson, Roger R. Reddel, Qing Zhong, Susana Vinga, Emanuel Gonçalves:
A technical review of multi-omics data integration methods: from classical statistical to deep generative approaches. - Syed Raza Abbas, Zeeshan Abbas, Arifa Zahir, Seung Won Lee:
Advancing genome-based precision medicine: a review on machine learning applications for rare genetic disorders. - Anqi Lin, Junpu Ye, Chang Qi, Lingxuan Zhu, Weiming Mou, Wenyi Gan, Dongqiang Zeng, Bufu Tang, Mingjia Xiao, Guangdi Chu, Shengkun Peng, Hank Z. H. Wong, Lin Zhang, Hengguo Zhang, Xinpei Deng, Kailai Li, Jian Zhang, Aimin Jiang, Zhengrui Li, Peng Luo:
Bridging artificial intelligence and biological sciences: a comprehensive review of large language models in bioinformatics. - Wenping Xie, Jingze Liu, Chuan Wang, Jiangyuan Wang, Wenjie Han, Yousong Peng, Xiangjun Du, Jing Meng, Kang Ning, Taijiao Jiang:
PREDAC-FluB: predicting antigenic clusters of seasonal influenza B viruses with protein language model embedding based convolutional neural network. - Yile Fu, Mohamad Youness, Alessia Virzì, Xinran Song, Michiel R. L. Tubeeckx, Gilles W. De Keulenaer, Hein Heidbuchel, Vincent F. M. Segers, Karin R. Sipido, Bernard Thienpont, H. Llewelyn Roderick:
Benchmarking of computational demultiplexing methods for single-nucleus RNA sequencing data. - Chenwei Zhang, Anne Condon, Khanh Dao Duc:
A comprehensive survey and benchmark of deep learning-based methods for atomic model building from cryo-electron microscopy density maps. - Hyunmin Woo, Seong-il Eyun:
Applications and techniques of single-cell RNA sequencing across diverse species. - Hansika Weerasena, Aruna Jayasena, Christina Boucher, Prabhat Mishra:
Formal verification of bioinformatics software using model checking and theorem proving. - Maik Wolfram-Schauerte, Thomas Vogel, Hanati Tuoken, Maria Faelth Savitski, Eric Simon, Kay Nieselt:
Approaching the holistic transcriptome - convolution and deconvolution in transcriptomics. - Xudong Guo, Zixu Ran, Fuyi Li:
Kinase-inhibitor binding affinity prediction with pretrained graph encoder and language model. - Erich Kummerfeld, Leland Williams, Yinzhao Wang, Samuel T. Peters, Elizabeth Schmidt, Mickayla Dufresne-To, David Bernlohr, Paul Robbins, Sayeed Ikramuddin, Oyedele Adeyi, Linshan Laux, Grant Barthel, Steven Johnson, Jinhua Wang, Laura Niedernhofer, Andrew Nelson, Constantin F. Aliferis:
Artifacts in spatial transcriptomics data: their detection, importance, prevalence, and prevention. - Yang Liu, Rongbo Shen, Lu Zhou, Qingyu Xiao, Jiao Yuan, Yixue Li:
A data-intelligence-intensive bioinformatics copilot system for large-scale omics research and scientific insights. - Ningyu Zhong, Zhihua Du:
NASNet-DTI: accurate drug-target interaction prediction using heterogeneous graphs and node adaptation. - Furong Qi, Qiang Huang, Yao Xuan, Yingyin Cao, Yunyun Shen, Yihan Ren, Zhe Liu, Zheng Zhang:
A roadmap for T cell receptor-peptide-bound major histocompatibility complex binding prediction by machine learning: glimpse and foresight.
Volume 26, Number 2, 2025
- Hailin Chen, Kuan Chen:
Ensemble learning based on matrix completion improves microbe-disease association prediction. - Minfang Song, Shuai Ma, Gong Wang, Yukun Wang, Zhenzhen Yang, Bin Xie, Tongkun Guo, Xingxu Huang, Liye Zhang:
Benchmarking copy number aberrations inference tools using single-cell multi-omics datasets. - Pengfei Zhu, Han Shu, Yongtian Wang, Xiaofeng Wang, Yuan Zhao, Jialu Hu, Jiajie Peng, Xuequn Shang, Zhen Tian, Jing Chen, Tao Wang:
MAEST: accurately spatial domain detection in spatial transcriptomics with graph masked autoencoder. - Mira Koul, Shalini Kaushik, Kavya Singh, Deepak Sharma:
VITALdb: to select the best viroinformatics tools for a desired virus or application. - Jing Zou, Wenyi Zhang, Jun Hu, Xiaogen Zhou, Biao Zhang:
DockEM: an enhanced method for atomic-scale protein-ligand docking refinement leveraging low-to-medium resolution cryo-EM density maps. - Yijun Mao, Jiale Wu, Jian Weng, Ming Li, Yunyan Xiong, Wanrong Gu, Rongjin Jiang, Rui Pang, Xudong Lin, Deyu Tang:
Inter-view contrastive learning and miRNA fusion for lncRNA-protein interaction prediction in heterogeneous graphs. - Ruijun Mao, Li Wan, Minghao Zhou, Dongxi Li:
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis. - Jinmiao Song, Yatong Hao, Shuang Zhao, Peng Zhang, Qilin Feng, Qiguo Dai, Xiaodong Duan:
Dual-stream cross-modal fusion alignment network for survival analysis. - Yongfei Hu, Xinyu Li, Ying Yi, Yan Huang, Guangyu Wang, Dong Wang:
Deep learning-driven survival prediction in pan-cancer studies by integrating multimodal histology-genomic data. - Carolina Monzó, Maider Aguerralde-Martin, Carlos Martínez-Mira, Angeles Arzalluz-Luque, Ana Conesa, Sonia Tarazona:
MOSim: bulk and single-cell multilayer regulatory network simulator. - Bo Li, Yongkang Zhao, Jing Hu, Shihua Zhang, Xiaolong Zhang:
scSAMAC: saliency-adjusted masking induced attention contrastive learning for single-cell clustering. - Jilong Bian, Hao Lu, Limin Wei, Yang Li, Guohua Wang:
Relational similarity-based graph contrastive learning for DTI prediction. - Kasmika Borah, Himanish Shekhar Das, Ram Kaji Budhathoki, Khursheed Aurangzeb, Saurav Mallik:
DOMSCNet: a deep learning model for the classification of stomach cancer using multi-layer omics data. - Wenhan Guo, Yuan Gao, Dan Du, Jason E. Sanchez, Yupeng Li, Weihong Qiu, Lin Li:
Elucidating the interactions between Kinesin-5/BimC and the microtubule: insights from TIRF microscopy and molecular dynamics simulations. - Nathaniel S. O'Connell, Byron C. Jaeger, Garrett S. Bullock, Jaime Lynn Speiser:
A comparison of random forest variable selection methods for regression modeling of continuous outcomes. - Maria Llambrich, Frans M. van der Kloet, Lluc Sementé, Anaïs Rodrigues, Saer Samanipour, Pierre-Hugues Stefanuto, Johan A. Westerhuis, Raquel Cumeras, Jesús Brezmes:
GcDUO: an open-source software for GC × GC-MS data analysis. - Sizhe Qiu, Bozhen Hu, Jing Zhao, Weiren Xu, Aidong Yang:
Seq2Topt: a sequence-based deep learning predictor of enzyme optimal temperature. - Gefei Zhao, Binbin Lai:
SC-VAR: a computational tool for interpreting polygenic disease risks using single-cell epigenomic data. - Xuexin Chen, Ruichu Cai, Zhengting Huang, Zijian Li, Jie Zheng, Min Wu:
Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers. - Adriano Fonzino, Pietro Luca Mazzacuva, Adam Handen, Domenico Alessandro Silvestris, Annette Arnold, Riccardo Pecori, Graziano Pesole, Ernesto Picardi:
REDInet: a temporal convolutional network-based classifier for A-to-I RNA editing detection harnessing million known events. - Jean-Pierre Borg, Jacques Colinge, Patrice Ravel:
Testing and overcoming the limitations of modular response analysis. - Meng Yuan, Seppe Goovaerts, Myoung K. Lee, Jay Devine, Stephen Richmond, Susan Walsh, Mark D. Shriver, John R. Shaffer, Mary L. Marazita, Hilde Peeters, Seth M. Weinberg, Peter Claes:
Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants. - Liang Chen, Madison Dautle, Ruoying Gao, Shaoqiang Zhang, Yong Chen:
Inferring gene regulatory networks from time-series scRNA-seq data via GRANGER causal recurrent autoencoders. - Yichong Li, Xiaoyong Pan, Hongbin Shen, Yang Yang:
DRAG: design RNAs as hierarchical graphs with reinforcement learning. - Saleh Sereshki, Stefano Lonardi:
Predicting differentially methylated cytosines in TET and DNMT3 knockout mutants via a large language model. - Duc Hai Nguyen, Woong-Ki Kim:
Disrupted microbial cross-feeding and altered L-phenylalanine consumption in people living with HIV. - Yuguang Li, Zhen Tian, Xiaofei Nan, Shoutao Zhang, Qinglei Zhou, Shuai Lu:
HSSPPI: hierarchical and spatial-sequential modeling for PPIs prediction. - Mingfei Han, Xiaoqing Chen, Xiao Li, Jie Ma, Tao Chen, Chunyuan Yang, Juan Wang, Yingxing Li, Wenting Guo, Yunping Zhu:
MulNet: a scalable framework for reconstructing intra- and intercellular signaling networks from bulk and single-cell RNA-seq data. - Correction to: STMGraph: spatial-context-aware of transcriptomes via a dual-remasked dynamic graph attention model.
- Yixuan Jin, Juanjuan Huang, Xu Sun, Yabo Fang, Jiageng Wu, Jianshi Du, Jiwei Jia, Guoqing Wang:
GiGs: graph-based integrated Gaussian kernel similarity for virus-drug association prediction. - Annette Spooner, Mohammad Karimi Moridani, Barbra Toplis, Jason Behary, Azadeh Safarchi, Salim Maher, Fatemeh Vafaee, Amany Zekry, Arcot Sowmya:
Benchmarking ensemble machine learning algorithms for multi-class, multi-omics data integration in clinical outcome prediction. - Xiaoyan Zhou, Luca Parisi, Wentao Huang, Yihan Zhang, Xiaoqun Huang, Mansour Youseffi, Farideh Javid, Renfei Ma:
A novel integrative multimodal classifier to enhance the diagnosis of Parkinson's disease. - Shuang Ge, Shuqing Sun, Huan Xu, Qiang Cheng, Zhixiang Ren:
Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective. - Yahao Wu, Jing Liu, Yanni Xiao, Shuqin Zhang, Limin Li:
CoupleVAE: coupled variational autoencoders for predicting perturbational single-cell RNA sequencing data. - Oleksandr Narykov, Yitan Zhu, Thomas S. Brettin, Yvonne A. Evrard, Alexander Partin, Fangfang Xia, Maulik Shukla, Priyanka Vasanthakumari, James H. Doroshow, Rick L. Stevens:
Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting. - Wei Xu, Gang Luo, Weiyu Meng, Xiaobing Zhai, Keli Zheng, Ji Wu, Yanrong Li, Abao Xing, Junrong Li, Zhifan Li, Ke Zheng, Kefeng Li:
MRAgent: an LLM-based automated agent for causal knowledge discovery in disease via Mendelian randomization. - Nicolaas F. V. Burger, Vittorio F. Nicolis, Anna-Maria Botha:
Evaluating long-read assemblers to assemble several aphididae genomes. - Abir Omran, Alexander Amberg, Gerhard F. Ecker:
Exploring diverse approaches for predicting interferon-gamma release: utilizing MHC class II and peptide sequences. - Laszlo Dobson, Gábor E. Tusnády, Peter Tompa:
Regularly updated benchmark sets for statistically correct evaluations of AlphaFold applications. - Shifu Luo, Hui Peng, Ying Shi, Jiaxin Cai, Songming Zhang, Ningyi Shao, Jinyan Li:
Integration of proteomics profiling data to facilitate discovery of cancer neoantigens: a survey. - Qi Dong, Yingying Guo, Chen Lv, Lingxue Ren, Bo Chen, Yan Wang, Yang Liu, Mingyue Liu, Kaidong Liu, Nan Zhang, Linzhu Wang, Shaocong Sang, Xin Li, Yang Hui, Haihai Liang, Yunyan Gu:
Unveiling a novel cancer hallmark by evaluation of neural infiltration in cancer. - Himansu Kumar, Abayomi Adegunlehin, Zikang Chen, Pora Kim:
FusionPub, a therapeutic landscape of human fusion genes. - Qiufeng Chen, Lijun Quan, Lexin Cao, Bei Zhang, Zhijun Zhang, Liangchen Peng, Junkai Wang, Yelu Jiang, Liangpeng Nie, Geng Li, Tingfang Wu, Qiang Lyu:
DS-MVP: identifying disease-specific pathogenicity of missense variants by pre-training representation. - Jair Herazo-Álvarez, Marco Mora, Sara Cuadros-Orellana, Karina Vilches-Ponce, Ruber Hernández-García:
A review of neural networks for metagenomic binning. - Xiaoyan Wang, Junwei Luo, Lili Wu, Huimin Luo, Fei Guo:
deepTAD: an approach for identifying topologically associated domains based on convolutional neural network and transformer model. - Emily C. Hector, Daiwei Zhang, Leqi Tian, Junning Feng, Xianyong Yin, Tianyi Xu, Markku Laakso, Yun Bai, Jiashun Xiao, Jian Kang, Tianwei Yu:
Dissecting genetic regulation of metabolic coordination. - Shrabanti Chowdhury, Sammy Ferri-Borgogno, Peng Yang, Wenyi Wang, Jie Peng, Samuel C. Mok, Pei Wang:
Learning directed acyclic graphs for ligands and receptors based on spatially resolved transcriptomic data of ovarian cancer. - Alessandra Aldieri, Thiranja Prasad Babarenda Gamage, Antonino Amedeo La Mattina, Axel Loewe, Francesco Pappalardo, Marco Viceconti:
Consensus statement on the credibility assessment of machine learning predictors. - Elise Jorge, Sylvain Foissac, Pierre Neuvial, Matthias Zytnicki, Nathalie Vialaneix:
A comprehensive review and benchmark of differential analysis tools for Hi-C data. - Hanwen Zhang, Deng Xiong, Xianggen Liu, Jiancheng Lv:
MolEM: a unified generative framework for molecular graphs and sequential orders. - Oleksandr Cherednichenko, Maria S. Poptsova:
Kolmogorov-Arnold networks for genomic tasks. - Zhen Gao, Yansen Su, Jin Tang, Huaiwan Jin, Yun Ding, Rui-Fen Cao, Pi-Jing Wei, Chun-Hou Zheng:
AttentionGRN: a functional and directed graph transformer for gene regulatory network reconstruction from scRNA-seq data. - De-Min Liang, Pu-Feng Du:
scMUG: deep clustering analysis of single-cell RNA-seq data on multiple gene functional modules. - Yunhui Qi, Xinyi Wang, Li-Xuan Qin:
Optimizing sample size for supervised machine learning with bulk transcriptomic sequencing: a learning curve approach. - Haolong Zeng, Chaoyi Yin, Chunyang Chai, Yuezhu Wang, Qi Dai, Huiyan Sun:
Cancer gene identification through integrating causal prompting large language model with omics data-driven causal inference. - Riikka Huusari, Tianduanyi Wang, Sándor Szedmák, Diogo Dias, Tero Aittokallio, Juho Rousu:
Scaling up drug combination surface prediction. - Qi Ge, Rui Qin, Shuang Liu, Quan Guo, Changcai Han, Weigang Chen:
Pragmatic soft-decision data readout of encoded large DNA. - Sijie Li, Heyang Hua, Shengquan Chen:
Graph neural networks for single-cell omics data: a review of approaches and applications. - Xusheng Ai, Melissa C. Smith, F. Alex Feltus:
GEMDiff: a diffusion workflow bridges between normal and tumor gene expression states: a breast cancer case study. - Bingqing Han, Yipeng Zhang, Longlong Li, Xinqi Gong, Kelin Xia:
TopoQA: a topological deep learning-based approach for protein complex structure interface quality assessment. - Jiashan Li, Xi Chen, He Huang, Mingliang Zeng, Jingcheng Yu, Xinqi Gong, Qiwei Ye:
$\mathcal{S}$ able: bridging the gap in protein structure understanding with an empowering and versatile pre-training paradigm. - Xuwen Wang, Zhili Chang, Yuqian Liu, Shenjie Wang, Xiaoyan Zhu, Yang Shao, Jiayin Wang:
EMcnv: enhancing CNV detection performance through ensemble strategies with heterogeneous meta-graph neural networks. - Peng Zhou, Zixiu Li, Feifan Liu, Euijin Kwon, Tien-Chan Hsieh, Shangyuan Ye, Shobha Vasudevan, Jung Ae Lee, Khanh-Van Tran, Chan Zhou:
BAMBI integrates biostatistical and artificial intelligence methods to improve RNA biomarker discovery. - Zhimin Li, Wenlan Chen, Hai Zhong, Cheng Liang:
PCLSurv: a prototypical contrastive learning-based multi-omics data integration model for cancer survival prediction. - Jie Ni, Bin Li, Shumei Miao, Xinting Zhang, Donghui Yan, Shengqi Jing, Shan Lu, Zhuoying Xie, Xin Zhang, Yun Liu:
MethPriorGCN: a deep learning tool for inferring DNA methylation prior knowledge and guiding personalized medicine.
Volume 26, Number 3, 2025
- Correction to: ProtGraph: a tool for the quick and comprehensive exploration and exploitation of the peptide search space derived from protein sequence databases using graphs.
- Luxuan Wang, Beihong Ji, Jingchen Zhai, Junmei Wang:
Advancing promiscuous aggregating inhibitor analysis with intelligent machine learning classification. - Lis Arend, Klaudia Adamowicz, Johannes R. Schmidt, Yuliya Burankova, Olga I. Zolotareva, Olga Tsoy, Josch Konstantin Pauling, Stefan Kalkhof, Jan Baumbach, Markus List, Tanja Laske:
Systematic evaluation of normalization approaches in tandem mass tag and label-free protein quantification data using PRONE. - Fengyi Guo, Yuanbo Li, Hongyuan Zhao, Xiaogang Liu, Jian Mao, Dongna Ma, Shuangping Liu:
GKNnet: an relational graph convolutional network-based method with knowledge-augmented activation layer for microbial structural variation detection. - Correction to: DOMSCNet: a deep learning model for the classification of stomach cancer using multi-layer omics data.
- Lianchong Gao, Yujun Liu, Jiawei Zou, Fulan Deng, Zheqi Liu, Zhen Zhang, Xinran Zhao, Lei Chen, Henry H. Y. Tong, Yuan Ji, Huangying Le, Xin Zou, Jie Hao:
Deep scSTAR: leveraging deep learning for the extraction and enhancement of phenotype-associated features from single-cell RNA sequencing and spatial transcriptomics data. - Mofan Feng, Liangjie Liu, Zhuo-Ning Xian, Xiaoxi Wei, Keyi Li, Wenqian Yan, Qing Lu, Yi Shi, Guang He:
PSTP: accurate residue-level phase separation prediction using protein conformational and language model embeddings. - Abrar Rahman Abir, Md Toki Tahmid, Rafiqul Islam Rayan, M. Saifur Rahman:
DeepRNA-Twist: language-model-guided RNA torsion angle prediction with attention-inception network. - Yuanyuan Zeng, Zhiyu You, Jiayang Guo, Jialin Zhao, Ying Zhou, Jialiang Huang, Xiaowen Lyu, Longbiao Chen, Qiyuan Li:
Chrombus-XMBD: a graph convolution model predicting 3D-genome from chromatin features. - Hao Tang, Feng Jiang, Zhi Zhang, Jiaojiao Yang, Lu Li, Qingye Zhang:
Metabolism-associated protein network constructing and host-directed anti-influenza drug repurposing.
Volume 26, Number 4, 2025
- Federico García-Criado, Pedro Seoane, Elena Rojano, Juan Garcia Ranea, James Richard Perkins:
Advancing edge-based clustering and graph embedding for biological network analysis: a case study in RASopathies. - Zahoor Ahmed, Kiran Shahzadi, Rui Li, Yu-Qing Jiang, Yan-Ting Jin, Muhammad Arif, Juan Feng:
An artificial intelligence-based approach for identifying the proteins regulating liquid-liquid phase separation. - Xin Xia, Yajie Zhang, Xiangxiang Zeng, Xing-yi Zhang, Chun-Hou Zheng, Yansen Su:
CMOMO: a deep multi-objective optimization framework for constrained molecular multi-property optimization. - Bin Lian, Haohui Zhang, Tao Wang, Yongtian Wang, Xuequn Shang, N. Ahmad Aziz, Jialu Hu:
Inference of gene coexpression networks from single-cell transcriptome data based on variance decomposition analysis. - Zhi Ran, Meilin Mu, Shaofeng Lin, Tao Wang, Jing Zeng, Lan Kuang, Kunqi Chen, Shengbao Suo, Kai Yuan, Hao-Dong Xu:
Deciphering the MHC immunopeptidome of human cancers with Ligand.MHC atlas. - Yun-Fei Ma, Ye Liu:
Intelligent Batch Epitope Identification and Partitioning: an intelligent tool for the identification of B cell dominant epitopes. - Genereux Akotenou, Achraf El Allali:
Genomic language models (gLMs) decode bacterial genomes for improved gene prediction and translation initiation site identification. - Jiani Ma, Zhikang Wang, Cen Tong, Qi Yang, Lin Zhang, Hui Liu:
pMHChat, characterizing the interactions between major histocompatibility complex class II molecules and peptides with large language models and deep hypergraph learning. - Youshu Cheng, Geyu Zhou, Hongyu Li, Xinyu Zhang, Amy Justice, Claudia Martinez, Bradley E. Aouizerat, Ke Xu, Hongyu Zhao:
Incorporating local ancestry information to predict genetically associated DNA methylation in admixed populations. - Tung Dang, Artem Lysenko, Keith A. Boroevich, Tatsuhiko Tsunoda:
VBayesMM: variational Bayesian neural network to prioritize important relationships of high-dimensional microbiome multiomics data. - Syed Sabih Ur Rehman, Muhammad Ibtisam Nasar, Cristina S. Mesquita, Souhaila Al Khodor, Richard A. Notebaart, Sascha Ott, Sunil Mundra, Ramesh P. Arasardanam, Khalid Muhammad, Mohammad Tauqeer Alam:
Integrative systems biology approaches for analyzing microbiome dysbiosis and species interactions. - Romana T. Pop, Ping-Han Hsieh, Tatiana Belova, Anthony Mathelier, Marieke L. Kuijjer:
Gene regulatory network integration with multi-omics data enhances survival predictions in cancer. - Junlong Liu, Jiaming Xiao, Xunwen Su, Yonglin Wang:
Deep learning-enhanced clustering and classification of protein molecule tertiary structures using weighted distance matrices. - Jing Li, Quan Zou, Chao Zhan:
AttenRNA: multi-scale deep attentive model with RNA feature variability analysis. - Zhiyang Hu, Linqiang Pan, Daijun Zhang, Yannan Bin, Yansen Su:
AEPMA: peptide-microbe association prediction based on autoevolutionary heterogeneous graph learning. - Maria Sindeeva, Alexander Telepov, Nikita Ivanisenko, Tatiana I Shashkova, Kuzma Khrabrov, Artem Tsypin, Artur Kadurin, Olga L. Kardymon:
AFToolkit: a framework for molecular modeling of proteins with AlphaFold-derived representations. - Qianyi Yan, Xuan Li, Jiangnan Cui, Jianming Rong, Jingsong Zhang, Pingting Gao, Yaochen Xu, Fufang Qiu, Chunman Zuo:
Spatial histology and gene-expression representation and generative learning via online self-distillation contrastive learning. - Ke Wu, Changming Sun, Jie Geng, Ping Wang, Qi Dai, Leyi Wei, Ran Su:
Iterative clustering algorithm G-DESC-E and pan-cancer key gene analysis based on single-cell sequencing data. - Yiyou Song, Bowen Song, Daiyun Huang, Anh Nguyen, Lihong Hu, Jia Meng, Yue Wang:
Multimodal zero-shot learning of previously unseen epitranscriptomes from RNA-seq data. - Qinglu Zhong, Kevin C. Chan, Lei Fu, Ruhong Zhou:
A free energy perturbation-assisted machine learning strategy for mimotope screening in neoantigen-based vaccine design. - Longyi Li, Liyan Dong, Hao Zhang, Dong Xu, Yongli Li:
spaLLM: enhancing spatial domain analysis in multi-omics data through large language model integration. - Xiaofei Zhao, Lei Wei, Xuegong Zhang:
Computational methods and data resources for predicting tumor neoantigens. - Hyejin Yu, Kwanyong Choi, Ji Yeon Kim, Sunyong Yoo:
Multi-level association rule mining and network pharmacology to identify the polypharmacological effects of herbal materials and compounds in traditional medicine. - Yao Dong, Jiaxue Zhang, Jin Shi, Yushan Hu, Xiaowen Cao, Yongfeng Dong, Xuekui Zhang:
scAGCI: an anchor graph-based method for cell clustering from integrated scRNA-seq and scATAC-seq data.
Volume 26, Number 5, 2025
- Carolin Charlotte Wendling, Marie Vasse, Sébastien Wielgoss:
Phage quest: a beginner's guide to explore viral diversity in the prokaryotic world. - Geng-Ming Hu, Hsin-Wei Chen, Chi-Ming Chen:
Mapping cancer heterogeneity: a consensus network approach to subtypes and pathways. - Yu Wang, Haichun Yang, Ruining Deng, Yuankai Huo, Qi Liu, Yu Shyr, Shilin Zhao:
stImage: a versatile framework for optimizing spatial transcriptomic analysis through customizable deep histology and location informed integration. - Yaowu Zhang, Xiu Jin, Xiaodan Zhang:
GCNMF-SDA: predicting snoRNA-disease associations based on graph convolution and non-negative matrix factorization. - Junlei Yu, Wenjia Gao, Siqi Chen, Ronglin Lu, Jianbo Qiao, Junru Jin, Leyi Wei, Hua Shi, Zilong Zhang, Feifei Cui, Xinbo Jiang, Zhongmin Yan:
MCAMEF-BERT: an efficient deep learning method for RNA N7-methylguanosine site prediction via multi-branch feature integration. - Yingxuan Ren, Fengtao Ren, Bo Yang:
Multi-layer matrix factorization for cancer subtyping using full and partial multi-omics dataset. - John Lee, Canh Hao Nguyen, Hiroshi Mamitsuka:
Beyond rigid docking: deep learning approaches for fully flexible protein-ligand interactions. - Rami Zakh, Alexander Churkin, Marina Parr, Tamir Tuller, Ohad Etzion, Harel Dahari, Danny Barash:
The bioinformatics of the finding that the hepatitis delta virus RNA editing mechanism by a conformational switch exists in genotype 7 in addition to genotype 3. - Guosheng Gu, Haowei Wu, Haojie Han, Zhiyi Lin, Yuping Sun, Guobo Xie, Qing Su, Zhenguo Liu:
MVSGDR: multi-view stacked graph convolutional network for drug repositioning. - Hongxu Zhu, Amir Asiaee, Leila Azinfar, Jun Li, Han Liang, Ehsan Irajizad, Kim-Anh Do, James P. Long:
AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes. - Youna Cho, Erin Kim, Minyoung Kim, Mina Rho:
DeepMobilome: predicting mobile genetic elements using sequencing reads of microbiomes. - Kailun Bai, Belaid Moa, Xiaojian Shao, Xuekui Zhang:
scSorterDL: a deep neural network-enhanced ensemble LDAs for single cell classifications. - Junxin Li, Chao Zhang, Wei Xia, Hei Wun Kan, Kaifang Huang, Sai Li, Mark Akinola Ige, Qiuliyang Yu, Jiawei Zhao, Xiaochun Wan, John Z. H. Zhang, Haiping Zhang:
Significantly enhancing human antibody affinity via deep learning and computational biology-guided single-point mutations. - Yanwen Shao, Zhihao Guo, Jinpeng Chen, Runsheng Li:
SLRanger: an integrated approach for spliced leader detection and operon prediction using long RNA reads. - Huayu Zhong, Juanji Wang, Xiaoxiao Liu, Xiaoyun Wei, Chengcheng Zhou, Taiyan Zou, Xin Han, Lingyun Mo, Wenling Qin, Yonghong Zhang:
A multi-dimensional computational framework of drug-induced hepatotoxicity: integrating molecular structure features with disease pathogenesis. - Xiang Li, Wei Peng, Xiaolei Zhu:
Predicting nucleic acid binding sites by attention map-guided graph convolutional network with protein language embeddings and physicochemical information. - Shenjie Wang, Xiaonan Wang, Xiaoyan Zhu, Xuwen Wang, Yuqian Liu, Minchao Zhao, Zhili Chang, Yang Shao, Haitao Zhang, Shuanying Yang, Jiayin Wang:
TMBquant: an explainable AI-powered caller advancing tumor mutation burden quantification across heterogeneous samples. - Linyang Jiang, Xiaodi Yang, Xiaokun Guo, Dianke Li, Jiajun Li, Stefan Wuchty, Wenyu Shi, Ziding Zhang:
Graph neural network integrated with pretrained protein language model for predicting human-virus protein-protein interactions. - Yinyin Gong, Rui Li, Yan Liu, Jilong Wang, Danny Z. Chen, Chee Keong Kwoh:
DeepPhosPPI: a deep learning framework with attention-CNN and transformer for predicting phosphorylation effects on protein-protein interactions. - Hao Wang, Guoqing Hu, Stephen S.-T. Yau:
Energy entropy vector: a novel approach for efficient microbial genomic sequence analysis and classification.
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