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ORCIDBIBM 2021: Houston, TX, USA
- Yufei Huang, Lukasz A. Kurgan, Feng Luo, Xiaohua Hu, Yidong Chen, Edward R. Dougherty, Andrzej Kloczkowski, Yaohang Li:
IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021, Houston, TX, USA, December 9-12, 2021. IEEE 2021, ISBN 978-1-6654-0126-5 - M. Madan Babu:
Abstract: Variation in GPCR signaling: Implications for drug discovery. 1-2 - Yubraj Gupta
, Carlos Costa, Eduardo Pinho, Luís A. Bastião Silva:
Improving the Visualization and Dicomization process for the Stacked Whole Slide Imaging. 1-8 - Arnaud Delorme, Jeffery A. Martin:
Automated Data Cleaning for the Muse EEG. 1-5 - Hongliu Yang, Matthias Eberlein, Jens Müller, Ronald Tetzlaff:
Seizure prediction with long-term iEEG recordings: What can we learn from data nonstationarity? 1-6 - James Geller, Navya Martin Kollapally:
Detecting, Reporting And Alleviating Racial Biases In Standardized Medical Terminologies And Ontologies. 1-5 - Li Shen:
Brain imaging genetics: integrated analysis and machine learning. 1 - Sai Mattapalli, Rishi Athavale:
ALLNet: A Hybrid Convolutional Neural Network to Improve Diagnosis of Acute Lymphocytic Leukemia (ALL) in White Blood Cells. 1-7 - Surabhi Mishra, Mahua Bhattacharya:
A combined Feature extraction technique for cancer classification based on deep learning approach. 1-7 - Richard H. Scheuermann:
Abstract: Explainable artificial intelligence and single cell genomics to understand the cellular complexity of human brain. 4 - Yihang Bao, Fei He, Weixi Wang, Han Wang, Minglong Dong:
Discover the Binding Domain of Transmembrane Proteins Based on Structural Universality. 5-11 - Cheng Chen, Yuguo Zha, Daming Zhu, Kang Ning, Xuefeng Cui:
Hydrogen bonds meet self-attention: all you need for protein structure embedding. 12-17 - Cheng Chen, Zongzhao Qiu, Zhenghe Yang, Bin Yu, Xuefeng Cui:
Jointly Learning to Align and Aggregate with Cross Attention Pooling for Peptide-MHC Class I Binding Prediction. 18-23 - Sheng Chen, Sen Zhang, Xiongjun Li, Yubao Liu, Yuedong Yang:
SEGEM: a Fast and Accurate Automated Protein Backbone Structure Modeling Method for Cryo-EM. 24-31 - Tiansu Gong, Fusong Ju, Shiwei Sun, Dongbo Bu:
SASA-Net: A spatial-aware self-attention mechanism for building protein 3D structure directly from inter-residue distances. 32-37 - Chen Jin, Zhuangwei Shi, Han Zhang, Yanbin Yin:
Predicting lncRNA-protein interactions based on graph autoencoders and collaborative training. 38-43 - Hailong Jin, Wei Du, Jiawei Gu, Tianhao Zhang, Xiaohu Shi:
Combining GCN and Bi-LSTM for Protein Secondary Structure Prediction. 44-49 - Matthew Kirchhof, Christopher J. F. Cameron, Stefan C. Kremer:
End-to-end chromosomal compartment prediction from reference genomes. 50-57 - Yawei Li, Qingyun Liu, Zexian Zeng, Yuan Luo:
Unsupervised clustering analysis of SARS-Cov-2 population structure reveals six major subtypes at early stage across the world. 58-63 - Sandun Rajapaksa, Dinithi Sumanaweera, Maria Garcia de la Banda, Peter J. Stuckey, David Abramson, Lloyd Allison, Arthur M. Lesk, Arun Siddharth Konagurthu:
On identifying statistical redundancy at the level of amino acid subsequences. 64-71 - Ali Sekmen, Kamal Al-Nasr, Christopher Jones:
Subspace Modeling for Classification of Protein Secondary Structure Elements from Cα Trace. 72-79 - Mengwei Sun, Yuqing Qian, Yijie Ding, Jijun Tang, Quan Zou:
Membrane Protein Identification via Multi-view Graph Regularized k-Local Hyperplane Distance Nearest Neighbor Model. 80-85 - Chengcheng Sun, Haitao Jiang:
An approximation algorithm for unifying adjacencies by double cut and joins in unsigned genomes. 86-91 - Yuxiao Wang, Zongzhao Qiu, Qihong Jiao, Cheng Chen, Zhaoxu Meng, Xuefeng Cui:
Structure-Based Protein-Drug Affinity Prediction with Spatial Attention Mechanisms. 92-97 - Min Zeng, Nian Wang, Yifan Wu, Yiming Li, Fang-Xiang Wu, Min Li:
Improving human essential protein prediction using only protein sequences via ensemble learning. 98-103 - Haiping Zhang, Tingting Zhang, Konda Mani Saravanan, Linbu Liao, Hao Wu, Haishan Zhang, Huiling Zhang, Yi Pan, Xuli Wu, Yanjie Wei:
A novel virtual drug screening pipeline with deep-leaning as core component identifies inhibitor of pancreatic alpha-amylase. 104-111 - Shuo Zhang, Changhuo Yang, Hong-Dong Li, Jianxin Wang:
GraphIsoFun: a graph neural network based approach for splice isoform function prediction. 112-117 - Pan Zhang, Shuangjia Zheng, Jianwen Chen, Yaoqi Zhou, Yuedong Yang:
DeepANIS: Predicting antibody paratope from concatenated CDR sequences by integrating bidirectional long-short-term memory and transformer neural networks. 118-124 - Xuecong Fu, Russell Schwartz:
ConTreeDP: A consensus method of tumor trees based on maximum directed partition support problem. 125-130 - He Huang, Chengshi Zeng, Xinqi Gong:
Inter-protein contact map generated only from intra-monomer by image inpainting. 131-136 - Lu Jiang, Jiahao Sun, Yue Wang, Qiao Ning, Na Luo, Minghao Yin:
Heterogeneous Graph Convolutional Network integrates Multi-modal Similarities for Drug-Target Interaction Prediction. 137-140 - Shuai Lu, Yuguang Li, Xiaofei Nan, Shoutao Zhang:
Attention-based Convolutional Neural Networks for Protein-Protein Interaction Site Prediction. 141-144 - Benjamin Soibam:
Deep learning predicts boundaries of topologically associated domains in human cell lines using CTCF, RAD21, and 12 epigenetic signals. 145-150 - Carlos Soto, Audrey Dalgarno, Darshan W. Bryner, Benjamin McLaughlin, Nicola Neretti, Anuj Srivastava:
Representation of Chromosome Conformations Using a Shape Alphabet Across Modeling Methods. 151-156 - Aakriti Upadhyay, Tuan Tran, Chinwe Ekenna:
A topology approach towards modeling activities and properties on a biomolecular surface. 157-162 - Xiangwen Wang, Yonggang Lu:
Heterogeneous Cryo-EM Projection Image Classification Based on Common Lines. 163-166 - Fu Wang, Liangliang Yuan, Yang Yang:
Predicting RNA-RBP Interactions by Using a Pseudo-Siamese Network. 167-170 - Jiamin Chen, Jianliang Gao, Tengfei Lyu, Babatounde Moctard Oloulade, Xiaohua Hu:
Multi-label Metabolic Pathway Prediction with Auto Molecular Structure Representation Learning. 171-176 - Jiechen Li, Xiangxiang Zeng, Yong Dou, Fei Xia, Shaoliang Peng:
LADstackING: Stacking Ensemble Learning-based Computational Model for Predicting Potential LncRNA-disease Associations. 177-182 - Dayun Liu, Yi Luo, Jingjing Zheng, Hanlin Xu, Jiaxuan Zhang, Lei Deng:
GCNSDA: Predicting snoRNA-disease associations via graph convolutional network. 183-188 - Jiawei Luo, Zihan Lai, Cong Shen, Pei Liu, Heyuan Shi:
Graph Attention Mechanism-based Deep Tensor Factorization for Predicting disease-associated miRNA-miRNA pairs. 189-196 - Cole A. Lyman, Matthew C. Morris, Spencer Richman, Hong Bao Cao, Antony Scerri, Chris Cheadle, Gordon Broderick:
High Fidelity Modeling of Pulse Dynamics using Logic Networks. 197-204 - Yurong Qian, Jingjing Zheng, Zhe Zhang, Ying Jiang, Jiaxuan Zhang, Lei Deng:
CMIVGSD: circRNA-miRNA Interaction Prediction Based on Variational Graph Auto-Encoder and Singular Value Decomposition. 205-210 - Haojiang Tan, Sichao Qiu, Jun Wang, Guoxian Yu, Wei Guo, Maozu Guo:
Genome-Phenome Association Prediction by Deep Factorizing Heterogeneous Molecular Network. 211-216 - Song Yu, Hanlin Xu, Yizhan Li, Dayun Liu, Lei Deng:
LGCMDS: Predicting miRNA-Drug Sensitivity based on Light Graph Convolution Network. 217-222 - Yanping Zeng, Xuhua Yan, Zhenlan Liang, Ruiqing Zheng, Min Li:
MKG: a mutual information based method to infer single cell gene regulatory network. 223-228 - Lingzhi Zhu, Guihua Duan, Cheng Yan, Jianxin Wang:
Identifying virus-receptor interactions through matrix completion with similarity fusion. 229-234 - Yun Zuo, Xiangrong Liu, Xiangxiang Zeng:
Pm6 A: an Integrated Classification Algorithm for 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Identifying m6 A Sites. 235-240 - Yaoran Chen, Yuanyuan Zhu, Ming Zhong, Juan Liu:
COMNA: Core-attachment based protein complex detection via multiple network alignment. 241-244 - Pujan Joshi, Honglin Wang, Salvatore Jaramillo, Seung-Hyun Hong, Charles Giardina, Dong-Guk Shin:
Identification of Crosstalk between Biological Pathway Routes in Cancer Cohorts. 245-248 - Faning Long, Xiaojun Ding, Xiaoqing Peng, Jianxin Wang, Xiaoshu Zhu:
SCOTCluster: Deep Clustering with Optimal Transport for Large-scale Single-cell RNA-seq Data. 249-252 - Lorenzo Martini, Roberta Bardini, Stefano Di Carlo:
Meta-Analysis of cortical inhibitory interneurons markers landscape and their performances in scRNA-seq studies. 253-258 - Advaith Nila Narayanan, Geervani Koneti:
An Efficient Methodology for PK-PD Data Analysis Based on Novel Bound Selection and Modified Spiral Dynamic Optimization Methods. 259-265 - Xia Sun, Chengcheng Fu, Suoqi Liu, Wenjie Chen, Ran Zhong, Tingting He, Xingpeng Jiang:
Multi-type Microbial Relation Extraction by Transfer Learning. 266-269 - Honglin Wang, Pujan Joshi, Seung-Hyun Hong, Dong-Ju Shin, Dong-Guk Shin:
ctBuilder: A framework for building pathway crosstalks by combining single cell data with bulk cell data. 270-273 - Xin Yu, Wenjun Wu, Pu Feng, Yongkai Tian:
Swarm Inverse Reinforcement Learning for Biological Systems. 274-279 - Junyao Zhang, Xiaogang Liu, Xiaoke Ma:
Temporal Link Prediction for Cancer Networks using Structural Consistency Regularized Non-negative Matrix Factorization. 280-283 - Aixiao Zou, Junzhong Ji:
Learning brain effective connectivity networks via controllable variational autoencoder. 284-287 - Yunfei Hu, V. Mangal Sanidhya, Lu Zhang, Zhou Xin:
An ensemble deep learning framework to refine large deletions in linked-reads. 288-295 - Chenchen Li, Jin Zhao, Haodi Feng, Daming Zhu:
TransCoord: Genome-guided Transcripts Assembly by Coordinating Candidate Paths into Two-phased Linear Programming. 296-301 - Zhenlan Liang, Ruiqing Zheng, Siqi Chen, Xuhua Yan, Min Li:
DeepCI: a deep learning based clustering method for single cell RNA-seq data. 302-307 - Zongzhao Qiu, Qihong Jiao, Yuxiao Wang, Cheng Chen, Daming Zhu, Xuefeng Cui:
rzMLP-DTA: gMLP network with ReZero for sequence-based drug-target affinity prediction. 308-313 - Xin Wang, Jun Wang, Guoxian Yu, Beibei Xin, Maozu Guo:
Maize Epistasis Detection by Multi-class Quantitative Multifactor Dimensionality Reduction. 314-319 - Yao-Zhong Zhang, Kiyoshi Yamaguchi, Sera Hatakeyama, Yoichi Furukawa, Satoru Miyano, Rui Yamaguchi, Seiya Imoto:
On the application of BERT models for nanopore methylation detection. 320-327 - Lan Huang, Hongrui Guan, Yanchun Liang, Renchu Guan, Xiaoyue Feng:
COVID-19 Knowledge Graph for Drug and Vaccine Development. 328-333 - Qihong Jiao, Zongzhao Qiu, Yuxiao Wang, Cheng Chen, Zhenghe Yang, Xuefeng Cui:
Edge-Gated Graph Neural Network for Predicting Protein-Ligand Binding Affinities. 334-339 - Zhirui Liao, Xiaodi Huang, Hiroshi Mamitsuka, Shanfeng Zhu:
Drug3D-DTI: Improved Drug-target Interaction Prediction by Incorporating Spatial Information of Small Molecules. 340-347 - Yu Wang, Hui Wang, Meijie Hou, Yaojun Wang, Dongbo Bu, Chunming Zhang, Chuncui Huang, Shiwei Sun:
Glycan immunogenicity prediction based on Graph neural network. 348-353 - Chunyu Wang, Yan Zhu, Naifeng Wen, Lingling Zhao, Junjie Wang:
SeqGO-CPA: Improving Compound-Protein Binding Affinity Prediction with Sequence Information and Gene Ontology Knowledge. 354-359 - Naveed Ahmed Azam, Jianshen Zhu, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search. 360-363 - Jonghwan Choi, Sangmin Seo, Jinuk Park, Sanghyun Park:
MolBit: De novo Drug Design via Binary Representations of SMILES for avoiding the Posterior Collapse Problem. 364-367 - Yuanyuan Deng, Song Yu, Lei Deng, Hui Liu, Xuejun Liu, Yi Luo:
A multi-task graph convolutional network modeling of drug-drug interactions and synergistic efficacy. 368-371 - Yuanqi Du, Yinkai Wang, Fardina Fathmiul Alam, Yuanjie Lu, Xiaojie Guo, Liang Zhao, Amarda Shehu:
Deep Latent-Variable Models for Controllable Molecule Generation. 372-375 - Natasha Danielle Sachiko L. De Guzman, Jose Alfonso C. Madroño, Marla A. Endriga, Enrique Jose L. Frio:
In Silico Docking of Traditional Chinese Medicine Compounds and Novel Redesigned Ligands to Pseudomonas aeruginosa Quinolone Signaling Proteins PqsA and PqsD. 376-380 - Zijing Liu, Xianbin Ye, Xiaoming Fang, Fan Wang, Hua Wu, Haifeng Wang:
Docking-based Virtual Screening with Multi-Task Learning. 381-385 - Chao Deng, Cui-Xiang Lin, Hong-Dong Li:
Improving the Prediction of Disease-associated Genes by Integrating Annotated Gene Sets. 386-391 - Mingliang Dou, Jijun Tang, Fei Guo:
Document-level DDI relation extraction with document-entity embedding. 392-397 - Fei He, Joshua Thompson, Ziting Mao, Yijie Ren, Yulia I. Nussbaum, Olha Kholod, Dmitriy Shin, Mark Hannink, Mihail Popescu, Dong Xu:
Identifying Genes and Their Interactions from Pathway Figures and Text in Biomedical Articles. 398-405 - Boya Ji, Jiawei Luo, Liangrui Pan, Xiaolan Xie, Shaoliang Peng:
DFL-PiDA: Prediction of Piwi-interacting RNA-Disease Associations based on Deep Feature Learning. 406-411 - Yankai Jiang, Lei Zhang, Yiming Li, Xiangyang He, Hanxiao Huang, Keqing Zhu, Yubo Tao, Hai Lin:
DeepNFT: Towards Precise Neurofibrillary Tangle Detection via Improving Multi-scale Feature Fusion and Adversary. 412-417 - Cui-Na Jiao, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, Chun-Hou Zheng, Xianzi Yu:
Sparse Hyper-graph Non-negative Matrix Factorization by Maximizing Correntropy. 418-423 - Xu Jin, MingMing Liu, WenQian He, Lin Wang, Ling Ma, Yalou Huang, Maoqiang Xie:
Prioritizing Disease Genes via Multi-View Nonnegative Matrix Factorization with Layer-Wise Explicit Hierarchical Constraint. 424-429 - Lanju Kong, Xiaolin Song, Qingqing Yin, Qingzhong Li:
OO-LSTM: A trusted medical transfers prediction model with on-chain and off-chain data fusion. 430-437 - Lishuang Li, Ruiyuan Lian, Hongbin Lu:
Document-Level Biomedical Relation Extraction with Generative Adversarial Network and Dual-Attention Multi-Instance Learning. 438-443 - Wei Li, Han Zhang, Qingqing Zhao, Jian Liu, Yanbin Yin:
Adversarial Dual-Channel Variational Graph Autoencoder for Synthetic Lethality Prediction in Human Cancers. 444-449 - Shuchen Li, Wei Wang, Jieyue He:
KGAPG: Knowledge-Aware Neural Group Representation Learning for Attentive Prescription Generation of Traditional Chinese Medicine. 450-455 - Bojing Li, Duo Zhong, Xingpeng Jiang, Tingting He:
TopoPhy-CNN: Integrating Topological Information of Phylogenetic Tree for Host Phenotype Prediction From Metagenomic Data. 456-461 - Pengyue Lin, Wen Yang, Siyuan Xia, Yu Jiang, Xiaoning Liu, Guohua Geng:
CFR-GAN: A Generative Model for Craniofacial Reconstruction. 462-469 - Wodan Ling, Youran Qi, Xing Hua, Michael C. Wu:
Deep ensemble learning over the microbial phylogenetic tree (DeepEn-Phy). 470-477 - Jian Liu, Zhi Qu, Yue Li, Jialiang Sun, Yongzhuang Liu:
Ontology-based annotation and retrieval for large-scale VCF data. 478-483 - Haoran Liu, Mingchao Shang, Huaxiang Zhang, Cheng Liang:
Cancer Subtype Identification based on Multi-view Subspace Clustering with Adaptive Local Structure Learning. 484-490 - Zhilong Lv, Yuexiao Lin, Rui Yan, Zhenghe Yang, Ying Wang, Fa Zhang:
PG-TFNet: Transformer-based Fusion Network Integrating Pathological Images and Genomic Data for Cancer Survival Analysis. 491-496 - Hehuan Ma, Yu Rong, Boyang Liu, Yuzhi Guo, Chaochao Yan, Junzhou Huang:
Gradient-Norm Based Attentive Loss for Molecular Property Prediction. 497-502 - Swati Padhee, Kimberly Swygert, Ian Micir:
Exploring Language Patterns in a Medical Licensure Exam Item Bank. 503-508 - Qian Qiao, Ying-Lian Gao, Shasha Yuan, Jin-Xing Liu:
Robust Tensor Method Based on Correntropy and Tensor Singular Value Decomposition for Cancer Genomics Data. 509-514 - Bin Quan, Manli Yang, Xia Li, Qinqun Chen, Guiqing Liu, Jiaming Hong, Zhifeng Hao, Li Li, Hang Wei:
Research on the Design of Active Learning Algorithm based on Query-by-Committee for Intelligent Fetal Monitoring. 515-521 - Siyuan Shen, Yurong Qian, Jingjing Zheng, Junyi Liu, Lei Deng:
Accurately Predicting circRNA-disease Associations Using Variational Graph Auto-encoders and LightGBM. 522-527 - Syed Fahad Sultan, Lilianne R. Mujica-Parodi, Steven Skiena:
NeuroPredictome: A Data-Driven Predictome Linking Neuroimaging to Phenotype. 528-535 - Xiaowei Wang, Jungang Han, Ben Li, Xiaoying Pan, Hui Xu:
Automatic ICD-10 Coding Based on Multi-Head Attention Mechanism and Gated Residual Network. 536-543 - Xuehong Wu, Junwen Duan, Jianhua Li, Min Li:
nPTAS: A Novel Platform for Text Annotation and Service. 544-549 - Weiming Xiang, Dong Chen, Yingbo Cui, Shaoliang Peng:
H-VAE: A Hybrid Variational AutoEncoder with Data Augmentation in Predicting CRISPR/Cas9 Off-target. 550-555 - Xiaohan Xing, Fan Yang, Hang Li, Jun Zhang, Yu Zhao, Mingxuan Gao, Junzhou Huang, Jianhua Yao:
An Interpretable Multi-Level Enhanced Graph Attention Network for Disease Diagnosis with Gene Expression Data. 556-561 - Yingze Xu, Yan Wang, Xuping Xie, Feilong Wang, Qiong Chen, Huiyan Sun:
An AutoEncoder-Based Matrix Factorization Approach to Estimating Cell Proportion from Bulk Tumor RNA-seq Data. 562-567 - Sisi Yang, Junzhong Ji, Xiaodan Zhang, Ying Liu, Zheng Wang:
Weakly Guided Hierarchical Encoder-Decoder Network for Brain CT Report Generation. 568-573 - Yaning Yang, Xiaoqi Wang, Ying Xu, Chao Yang, Bin Jiang, Shaoliang Peng:
ParaPindel: a scalable coordinated parallel detection framework for human genome-wide structural variation. 574-579 - Xiang Yue, Xinliang Frederick Zhang, Ziyu Yao, Simon M. Lin, Huan Sun:
CliniQG4QA: Generating Diverse Questions for Domain Adaptation of Clinical Question Answering. 580-587 - Shuo Zhang, Xiaoli Lin, Xiaolong Zhang:
Discovering DTI and DDI by Knowledge Graph with MHRW and Improved Neural Network. 588-593 - Yongqing Zhang, Zixuan Wang, Yuhang Liu, Libo Lu, Xiaoyao Tan, Quan Zou:
By hybrid neural networks for prediction and interpretation of transcription factor binding sites based on multi-omics. 594-599 - Shilong Zhang, Yue Tang, Jing Yan, Linye Li, Tong Li, Jixiang Li, Peilin Xie, Yuanshuai Gu, Jiakang Xu, Zaiwen Feng, Wen Zhang, Jingbo Xia, Wolfgang Mayer, Hong-Yu Zhang, Guang-Cun He, Keqing He:
A Graph-based Approach for Integrating Biological Heterogeneous Data Based on Connecting Ontology. 600-607 - Yu Zhao, Yidan Zhang, Zhi-An Huang, Fan Yang, Lei Duan, Jianhua Yao:
Mining the Associations between V(D)J Gene Segments and COVID-19 Disease Characteristics. 608-613 - Yiqing Zhao, Michael G. Ison, Yuan Luo:
COVID Vaccine and Cardiovascular Risks: A Natural Language Analysis of Vaccine Adverse Event Reports. 614-618 - Yao Zhao, Weizhong Zhao, Xingpeng Jiang, Tingting He, Bianping Su:
An improved RL-based framework for multiple biomedical event extraction via self-supervised learning. 619-624 - Qingqing Zhu, Pengfei Wu, Zhouxing Tan, Jiaxin Duan, Dongyan Zhao, Junfei Liu:
Knowledge Distillation with Metric Learning for Medical Dialogue Generation. 625-632