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ORCIDJournal of Cheminformatics, Volume 16
Volume 16, Number 1, December 2024
- Soyeon Lee, Sunyong Yoo
:
InterDILI: interpretable prediction of drug-induced liver injury through permutation feature importance and attention mechanism. 1 - Debby D. Wang, Wenhui Wu, Ran Wang:
Structure-based, deep-learning models for protein-ligand binding affinity prediction. 2 - Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel M. Morkisz, Stanislaw Jastrzebski:
Relative molecule self-attention transformer. 3 - Yaxin Gu, Yimeng Wang, Keyun Zhu, Weihua Li, Guixia Liu, Yun Tang:
DBPP-Predictor: a novel strategy for prediction of chemical drug-likeness based on property profiles. 4 - Sadettin Y. Ugurlu, David W. McDonald, Huangshu Lei, Alan M. Jones, Shu Li, Henry H. Y. Tong, Mark S. Butler, Shan He:
Cobdock: an accurate and practical machine learning-based consensus blind docking method. 5 - Barbara Zdrazil, Rajarshi Guha, Karina Martínez-Mayorga, Nina Jeliazkova:
Are new ideas harder to find? A note on incremental research and Journal of Cheminformatics' Scientific Contribution Statement. 6 - Tinghao Zhang, Shaohua Sun, Runzhou Wang, Ting Li, Bicheng Gan, Yuezhou Zhang:
BioisoIdentifier: an online free tool to investigate local structural replacements from PDB. 7 - Sadjad Fakouri Baygi, Dinesh Kumar Barupal:
IDSL_MINT: a deep learning framework to predict molecular fingerprints from mass spectra. 8 - Paula Carracedo-Reboredo, Eider Aranzamendi, Shan He, Sonia Arrasate, Cristian R. Munteanu, Carlos Fernandez-Lozano, Nuria Sotomayor, Esther Lete, Humberto González Díaz:
MATEO: intermolecular α-amidoalkylation theoretical enantioselectivity optimization. Online tool for selection and design of chiral catalysts and products. 9 - Wei-Cheng Huang, Wei-Ting Lin, Ming-Shiu Hung, Jinq-Chyi Lee, Chun-Wei Tung:
Decrypting orphan GPCR drug discovery via multitask learning. 10 - Lung-Yi Chen, Yi-Pei Li:
Enhancing chemical synthesis: a two-stage deep neural network for predicting feasible reaction conditions. 11 - Anuj Gahlawat, Anjali Singh, Hardeep Sandhu, Prabha Garg:
CRAFT: a web-integrated cavity prediction tool based on flow transfer algorithm. 12 - Jiangxia Wu, Yihao Chen, Jingxing Wu, Duancheng Zhao, Jindi Huang, MuJie Lin, Ling Wang:
Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors. 13 - Jonghyun Lee, Dae Won Jun, Ildae Song, Yun Kim:
DLM-DTI: a dual language model for the prediction of drug-target interaction with hint-based learning. 14 - Derek Long, Liam Eade, Matthew P. Sullivan, Katharina Dost, Samuel M. Meier-Menches, David C. Goldstone, Christian G. Hartinger, Jörg S. Wicker, Katerina Taskova:
AdductHunter: identifying protein-metal complex adducts in mass spectra. 15 - Alexander S. Behr, Hendrik Borgelt, Norbert Kockmann:
Ontologies4Cat: investigating the landscape of ontologies for catalysis research data management. 16 - Kamel Mansouri, José T. Moreira-Filho, Charles N. Lowe, Nathaniel Charest, Todd Martin, Valery Tkachenko, Richard S. Judson, Mike Conway, Nicole C. Kleinstreuer, Antony J. Williams:
Free and open-source QSAR-ready workflow for automated standardization of chemical structures in support of QSAR modeling. 19 - Candida Manelfi, Valerio Tazzari, Filippo Lunghini, Carmen Cerchia, Anna Fava, Alessandro Pedretti, Pieter F. W. Stouten, Giulio Vistoli, Andrea Rosario Beccari:
"DompeKeys": a set of novel substructure-based descriptors for efficient chemical space mapping, development and structural interpretation of machine learning models, and indexing of large databases. 21 - Runhan Shi, Gufeng Yu, Xiaohong Huo, Yang Yang:
Prediction of chemical reaction yields with large-scale multi-view pre-training. 22 - Olivier Beyens, Hans De Winter:
Preventing lipophilic aggregation in cosolvent molecular dynamics simulations with hydrophobic probes using Plumed Automatic Restraining Tool (PART). 23 - Adrià Cereto-Massagué, Santiago Garcia-Vallvé, Gerard Pujadas:
Correction: DecoyFinder, a tool for finding decoy molecules. 24 - Jongmin Han, Youngchun Kwon, Youn-Suk Choi, Seokho Kang:
Improving chemical reaction yield prediction using pre-trained graph neural networks. 25 - Marie Oestreich, Iva Ewert, Matthias Becker:
Small molecule autoencoders: architecture engineering to optimize latent space utility and sustainability. 26 - Karina Beatriz Jimenes Vargas, Alejandro Pazos, Cristian R. Munteanu, Yunierkis Pérez-Castillo, Eduardo Tejera:
Prediction of compound-target interaction using several artificial intelligence algorithms and comparison with a consensus-based strategy. 27 - Sabrina Jaeger-Honz, Karsten Klein, Falk Schreiber:
Systematic analysis, aggregation and visualisation of interaction fingerprints for molecular dynamics simulation data. 28 - Bowen Tang, Zhangming Niu, Xiaofeng Wang, Junjie Huang, Chao Ma, Jing Peng, Yinghui Jiang, Ruiquan Ge, Hongyu Hu, Luhao Lin, Guang Yang:
Automated molecular structure segmentation from documents using ChemSAM. 29 - Tsuyoshi Esaki, Tomoki Yonezawa, Kazuyoshi Ikeda:
A new workflow for the effective curation of membrane permeability data from open ADME information. 30 - Alex K. Chew, Matthew Sender, Zachary Kaplan, Anand Chandrasekaran, Jackson Chief Elk, Andrea R. Browning, H. Shaun Kwak, Mathew D. Halls, Mohammad Atif Faiz Afzal:
Advancing material property prediction: using physics-informed machine learning models for viscosity. 31 - Anna Carbery, Martin Buttenschoen, Rachael Skyner, Frank von Delft, Charlotte M. Deane:
Learnt representations of proteins can be used for accurate prediction of small molecule binding sites on experimentally determined and predicted protein structures. 32 - Lingling Shen, Jian Fang, Lulu Liu, Fei Yang, Jeremy L. Jenkins, Peter S. Kutchukian, He Wang:
Pocket Crafter: a 3D generative modeling based workflow for the rapid generation of hit molecules in drug discovery. 33 - Matteo Krüger, Ashmi Mishra, Peter Spichtinger, Ulrich Pöschl, Thomas Berkemeier:
A numerical compass for experiment design in chemical kinetics and molecular property estimation. 34 - Davide Boldini, Davide Ballabio, Viviana Consonni, Roberto Todeschini, Francesca Grisoni, Stephan A. Sieber:
Effectiveness of molecular fingerprints for exploring the chemical space of natural products. 35 - Thomas E. Lockwood, Alexander Angeloski:
DGet! An open source deuteration calculator for mass spectrometry data. 36 - Maarten R. Dobbelaere, István Lengyel, Christian V. Stevens, Kevin M. Van Geem:
Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices. 37 - Wenjia Qian, Xiaorui Wang, Yu Kang, Peichen Pan, Tingjun Hou, Chang-Yu Hsieh:
A general model for predicting enzyme functions based on enzymatic reactions. 38 - Peter B. R. Hartog, Fabian Krüger, Samuel Genheden, Igor V. Tetko:
Using test-time augmentation to investigate explainable AI: inconsistencies between method, model and human intuition. 39 - Klaudia Caba, Viet-Khoa Tran-Nguyen, Taufiq Rahman, Pedro J. Ballester:
Comprehensive machine learning boosts structure-based virtual screening for PARP1 inhibitors. 40 - Xinwei Zhao, Junqing Xu, Youyuan Shui, Mengdie Xu, Jie Hu, Xiaoyan Liu, Kai Che, Junjie Wang, Yun Liu:
PermuteDDS: a permutable feature fusion network for drug-drug synergy prediction. 41 - Michael Blakey, Samantha Kanza, Jeremy G. Frey:
Zombie cheminformatics: extraction and conversion of Wiswesser Line Notation (WLN) from chemical documents. 42 - Sébastien J. J. Guesné, Thierry Hanser, Stéphane Werner, Samuel Boobier, Shaylyn Scott:
Mind your prevalence! 43 - Ming Du, Xingran Xie, Jing Luo, Jin Li:
Meta-learning-based Inductive logistic matrix completion for prediction of kinase inhibitors. 44 - Satnam Singh, Gina Zeh, Jessica Freiherr, Thilo Bauer, Isik Türkmen, Andreas Grasskamp:
Classification of substances by health hazard using deep neural networks and molecular electron densities. 45 - Maryam Astero, Juho Rousu:
Learning symmetry-aware atom mapping in chemical reactions through deep graph matching. 46 - Zixin Zhuang, Amanda S. Barnard:
Classification of battery compounds using structure-free Mendeleev encodings. 47 - Zhijiang Yang, Tengxin Huang, Li Pan, Jingjing Wang, Liangliang Wang, Junjie Ding, Junhua Xiao:
QuanDB: a quantum chemical property database towards enhancing 3D molecular representation learning. 48 - Jeaphianne P. M. van Rijn, Marvin Martens, Ammar Ammar, Mihaela Roxana Cimpan, Valerie Fessard, Peter Hoet, Nina Jeliazkova, Sivakumar Murugadoss, Ivana Vinkovic Vrcek, Egon L. Willighagen:
From papers to RDF-based integration of physicochemical data and adverse outcome pathways for nanomaterials. 49 - Nomagugu B. Ncube, Matshawandile Tukulula, Krishna G. Govender:
Leveraging computational tools to combat malaria: assessment and development of new therapeutics. 50 - Christina Humer, Rachel Nicholls, Henry Heberle, Moritz Heckmann, Michael Pühringer, Thomas Wolf, Maximilian Lübbesmeyer, Julian Heinrich, Julius Hillenbrand, Giulio Volpin, Marc Streit:
CIME4R: Exploring iterative, AI-guided chemical reaction optimization campaigns in their parameter space. 51 - Julia Rahman, M. A. Hakim Newton, Mohammed Eunus Ali, Abdul Sattar:
Distance plus attention for binding affinity prediction. 52 - Markus Orsi, Jean-Louis Reymond:
One chiral fingerprint to find them all. 53 - Hunter N. B. Moseley, Philippe Rocca-Serra, Reza M. Salek, Masanori Arita, Emma Schymanski:
InChI isotopologue and isotopomer specifications. 54 - Hengwei Chen, Jürgen Bajorath:
Generative design of compounds with desired potency from target protein sequences using a multimodal biochemical language model. 55 - Zachary A. Rollins, Alan C. Cheng, Essam Metwally:
MolPROP: Molecular Property prediction with multimodal language and graph fusion. 56 - Lakshidaa Saigiridharan, Alan Kai Hassen, Helen Lai, Paula Torren-Peraire, Ola Engkvist, Samuel Genheden:
AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application. 57 - David Meijer, Marnix H. Medema, Justin J. J. van der Hooft:
CineMol: a programmatically accessible direct-to-SVG 3D small molecule drawer. 58 - Hocheol Lim:
Development of scoring-assisted generative exploration (SAGE) and its application to dual inhibitor design for acetylcholinesterase and monoamine oxidase B. 59 - Joseph Heeley, Samuel Boobier, Jonathan D. Hirst:
Solvent flashcards: a visualisation tool for sustainable chemistry. 60 - Danh Bui Thi, Youzhong Liu, Jennifer L. Lippens, Kris Laukens, Thomas De Vijlder:
TransExION: a transformer based explainable similarity metric for comparing IONS in tandem mass spectrometry. 61 - Said Moshawih, Zhen Hui Bu, Hui Poh Goh, Nurolaini Kifli, Lam Hong Lee, Khang Wen Goh, Chiau Ming Long:
Consensus holistic virtual screening for drug discovery: a novel machine learning model approach. 62 - Reagan M. Mogire, Silviane A. Miruka, Dennis W. Juma, Case W. McNamara, Ben Andagalu, Jeremy N. Burrows, Elodie Chenu, James Duffy, Bernhards Ogutu, Hoseah M. Akala:
Protein target similarity is positive predictor of in vitro antipathogenic activity: a drug repurposing strategy for Plasmodium falciparum. 63 - Morgan C. Thomas, Noel M. O'Boyle, Andreas Bender, Chris de Graaf:
MolScore: a scoring, evaluation and benchmarking framework for generative models in de novo drug design. 64 - Trevor N. Brown, Alessandro Sangion, Jon A. Arnot:
Identifying uncertainty in physical-chemical property estimation with IFSQSAR. 65 - Jeevan Kandel, Palistha Shrestha, Hilal Tayara, Kil To Chong:
PUResNetV2.0: a deep learning model leveraging sparse representation for improved ligand binding site prediction. 66 - Yufang Zhang, Jiayi Li, Shenggeng Lin, Jianwei Zhao, Yi Xiong, Dong-Qing Wei:
An end-to-end method for predicting compound-protein interactions based on simplified homogeneous graph convolutional network and pre-trained language model. 67 - Zhijiang Yang, Tengxin Huang, Li Pan, Jingjing Wang, Liangliang Wang, Junjie Ding, Junhua Xiao:
Correction: QuanDB: a quantum chemical property database towards enhancing 3D molecular representation learning. 68 - Sunghwan Kim, Bo Yu, Qingliang Li, Evan E. Bolton:
PubChem synonym filtering process using crowdsourcing. 69 - Arnau Comajuncosa-Creus, Aksel Lenes, Miguel Sánchez-Palomino, Dylan Dalton, Patrick Aloy:
Stereochemically-aware bioactivity descriptors for uncharacterized chemical compounds. 70 - Xiaofan Zheng, Yoichi Tomiura:
A BERT-based pretraining model for extracting molecular structural information from a SMILES sequence. 71 - Elena Bandini, Rodrigo Castellano Ontiveros, Ardiana Kajtazi, Hamed Eghbali, Frédéric Lynen:
Physicochemical modelling of the retention mechanism of temperature-responsive polymeric columns for HPLC through machine learning algorithms. 72 - Niklas Dobberstein, Astrid Maass, Jan Hamaekers:
Llamol: a dynamic multi-conditional generative transformer for de novo molecular design. 73 - Lung-Yi Chen, Yi-Pei Li:
AutoTemplate: enhancing chemical reaction datasets for machine learning applications in organic chemistry. 74 - Staffan Arvidsson McShane, Ulf Norinder, Jonathan Alvarsson, Ernst Ahlberg, Lars Carlsson, Ola Spjuth:
CPSign: conformal prediction for cheminformatics modeling. 75 - Zihui Huang, Liqiang He, Yuhang Yang, Andi Li, Zhiwen Zhang, Siwei Wu, Yang Wang, Yan He, Xujie Liu:
Application of machine reading comprehension techniques for named entity recognition in materials science. 76 - Morgan Thomas, Mazen Ahmad, Gary Tresadern, Gianni De Fabritiis:
PromptSMILES: prompting for scaffold decoration and fragment linking in chemical language models. 77 - Kohulan Rajan, Henning Otto Brinkhaus, Achim Zielesny, Christoph Steinbeck:
Advancements in hand-drawn chemical structure recognition through an enhanced DECIMER architecture. 78 - Ruifeng Zhou, Jing Fan, Sishu Li, Wenjie Zeng, Yilun Chen, Xiaoshan Zheng, Hongyang Chen, Jun Liao:
LVPocket: integrated 3D global-local information to protein binding pockets prediction with transfer learning of protein structure classification. 79 - Kaipeng Zeng, Bo Yang, Xin Zhao, Yu Zhang, Fan Nie, Xiaokang Yang, Yaohui Jin, Yanyan Xu:
Ualign: pushing the limit of template-free retrosynthesis prediction with unsupervised SMILES alignment. 80 - Raghad Al-Jarf, Carlos H. M. Rodrigues, Yoochan Myung, Douglas E. V. Pires, David B. Ascher:
piscesCSM: prediction of anticancer synergistic drug combinations. 81 - Tieu-Long Phan, Klaus Weinbauer, Thomas Gärtner, Daniel Merkle, Jakob L. Andersen, Rolf Fagerberg, Peter F. Stadler:
Reaction rebalancing: a novel approach to curating reaction databases. 82 - Shuan Chen, Yousung Jung:
Estimating the synthetic accessibility of molecules with building block and reaction-aware SAScore. 83 - Karla P. Godinez-Macias, Elizabeth A. Winzeler:
CACTI: an in silico chemical analysis tool through the integration of chemogenomic data and clustering analysis. 84 - Vishal Dey, Xia Ning:
Enhancing molecular property prediction with auxiliary learning and task-specific adaptation. 85 - Rayyan T. Khan, Petra Pokorna, Jan Stourac, Simeon Borko, Ihor Arefiev, Joan Planas-Iglesias, Adam Dobias, Gaspar R. P. Pinto, Veronika Szotkowska, Jaroslav Sterba, Ondrej Slaby, Jirí Damborský, Stanislav Mazurenko, David Bednar:
A computational workflow for analysis of missense mutations in precision oncology. 86 - Gergely Zahoránszky-Köhalmi, Kanny K. Wan, Alexander G. Godfrey:
Hilbert-curve assisted structure embedding method. 87 - Niek F. de Jonge, Helge Hecht, Michael Strobel, Mingxun Wang, Justin J. J. van der Hooft, Florian Huber:
Reproducible MS/MS library cleaning pipeline in matchms. 88 - Chengwei Zhang, Yushuang Zhai, Ziyang Gong, Hongliang Duan, Yuan-Bin She, Yun-Fang Yang, An Su:
Transfer learning across different chemical domains: virtual screening of organic materials with deep learning models pretrained on small molecule and chemical reaction data. 89 - Louis Plyer, Gilles Marcou, Céline Perves, Fanny Bonachéra, Alexandre Varnek:
Implementation of a soft grading system for chemistry in a Moodle plugin: reaction handling. 90 - Run-Hsin Lin, Pinpin Lin, Chia-Chi Wang, Chun-Wei Tung:
A novel multitask learning algorithm for tasks with distinct chemical space: zebrafish toxicity prediction as an example. 91 - Yang Tan, Mingchen Li, Ziyi Zhou, Pan Tan, Huiqun Yu, Guisheng Fan, Liang Hong:
PETA: evaluating the impact of protein transfer learning with sub-word tokenization on downstream applications. 92 - Jasmin Hafner, Tim Lorsbach, Sebastian Schmidt, Liam Brydon, Katharina Dost, Kunyang Zhang, Kathrin Fenner, Jörg Wicker:
Advancements in biotransformation pathway prediction: enhancements, datasets, and novel functionalities in enviPath. 93 - Xiuyuan Hu, Guoqing Liu, Quanming Yao, Yang Zhao, Hao Zhang:
Hamiltonian diversity: effectively measuring molecular diversity by shortest Hamiltonian circuits. 94 - Jiazhen He, Alessandro Tibo, Jon Paul Janet, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist:
Evaluation of reinforcement learning in transformer-based molecular design. 95 - Felix Bänsch, Mirco Daniel, Harald Lanig, Christoph Steinbeck, Achim Zielesny:
An automated calculation pipeline for differential pair interaction energies with molecular force fields using the Tinker Molecular Modeling Package. 96 - Paola Moyano-Gómez, Jukka V. Lehtonen, Olli T. Pentikäinen, Pekka A. Postila:
Building shape-focused pharmacophore models for effective docking screening. 97 - Sergey Sosnin:
MolCompass: multi-tool for the navigation in chemical space and visual validation of QSAR/QSPR models. 98 - Maarten R. Dobbelaere, István Lengyel, Christian V. Stevens, Kevin M. Van Geem:
Geometric deep learning for molecular property predictions with chemical accuracy across chemical space. 99 - Janosch Menke, Yasmine Nahal, Esben Jannik Bjerrum, Mikhail Kabeshov, Samuel Kaski, Ola Engkvist:
Metis: a python-based user interface to collect expert feedback for generative chemistry models. 100 - José T. Moreira-Filho, Dhruv Ranganath, Mike Conway, Charles Schmitt, Nicole C. Kleinstreuer, Kamel Mansouri:
Democratizing cheminformatics: interpretable chemical grouping using an automated KNIME workflow. 101 - Fiona C. Y. Yu, Jorge L. Galvez Vallejo, Giuseppe M. J. Barca:
Automatic molecular fragmentation by evolutionary optimisation. 102 - Yuto Ohnuki, Manato Akiyama, Yasubumi Sakakibara:
Deep learning of multimodal networks with topological regularization for drug repositioning. 103 - Noah Kleinschmidt, Thomas Lemmin:
BuildAMol: a versatile Python toolkit for fragment-based molecular design. 104 - Chloe Engler Hart, António J. Preto, Shaurya Chanana, David Healey, Tobias Kind, Daniel Domingo-Fernández:
Evaluating the generalizability of graph neural networks for predicting collision cross section. 105 - Barbara R. Terlouw, Friederike Biermann, Sophie P. J. M. Vromans, Elham Zamani, Eric J. N. Helfrich, Marnix H. Medema:
RAIChU: automating the visualisation of natural product biosynthesis. 106 - Zhiguang Fan, Yuedong Yang, Mingyuan Xu, Hongming Chen:
EC-Conf: A ultra-fast diffusion model for molecular conformation generation with equivariant consistency. 107 - Sven Marcel Stefan, Katja Stefan, Vigneshwaran Namasivayam:
Computer-aided pattern scoring (C@PS): a novel cheminformatic workflow to predict ligands with rare modes-of-action. 108 - Luis H. M. Torres, Joel P. Arrais, Bernardete Ribeiro:
Combining graph neural networks and transformers for few-shot nuclear receptor binding activity prediction. 109 - Samar Monem, Aboul Ella Hassanien, Alaa H. Abdel-Hamid:
A multi-view feature representation for predicting drugs combination synergy based on ensemble and multi-task attention models. 110 - Prashant Srivastava, Alexandra Steuer, Francesco Ferri, Alessandro Nicoli, Kristian Schultz, Saptarshi Bej, Antonella Di Pizio, Olaf Wolkenhauer:
Bitter peptide prediction using graph neural networks. 111 - Sejal Sharma, Liping Feng, Nicha Boonpattrawong, Arvinder Kapur, Lisa Barroilhet, Manish S. Patankar, Spencer S. Ericksen:
Data mining of PubChem bioassay records reveals diverse OXPHOS inhibitory chemotypes as potential therapeutic agents against ovarian cancer. 112 - Yuting Liu, Akiyasu C. Yoshizawa, Yiwei Ling, Shujiro Okuda:
Insights into predicting small molecule retention times in liquid chromatography using deep learning. 113 - Ondrej Vavra, Jonathan D. Tyzack, Farzan Haddadi, Jan Stourac, Jirí Damborský, Stanislav Mazurenko, Janet M. Thornton, David Bednar:
Large-scale annotation of biochemically relevant pockets and tunnels in cognate enzyme-ligand complexes. 114 - Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado:
Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization. 115