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Journal of Cheminformatics, Volume 14
Volume 14, Number 1, December 2022
- Min Wei, Xudong Zhang, Xiaolin Pan
, Bo Wang, Changge Ji, Yifei Qi
, John Z. H. Zhang:
HobPre: accurate prediction of human oral bioavailability for small molecules. 1 - Youngchun Kwon, Dongseon Lee, Youn-Suk Choi, Seokho Kang
:
Uncertainty-aware prediction of chemical reaction yields with graph neural networks. 2 - Alan Kerstjens, Hans De Winter
:
LEADD: Lamarckian evolutionary algorithm for de novo drug design. 3 - Hadar Grimberg, Vinay S. Tiwari
, Benjamin Tam, Lihi Gur-Arie, Daniela Gingold, Lea Polachek, Barak Akabayov
:
Machine learning approaches to optimize small-molecule inhibitors for RNA targeting. 4 - Ingoo Lee
, Hojung Nam
:
Sequence-based prediction of protein binding regions and drug-target interactions. 5 - Miao Yu
, Georgia Dolios, Lauren Petrick:
Reproducible untargeted metabolomics workflow for exhaustive MS2 data acquisition of MS1 features. 6 - Michael Freitas Gustavo
, Toon Verstraelen
:
GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations. 7 - Ammar Ammar
, Rachel Cavill
, Chris T. A. Evelo, Egon L. Willighagen
:
PSnpBind: a database of mutated binding site protein-ligand complexes constructed using a multithreaded virtual screening workflow. 8 - Eunyoung Kim, Hojung Nam
:
DeSIDE-DDI: interpretable prediction of drug-drug interactions using drug-induced gene expressions. 9 - Arash Keshavarzi Arshadi
, Milad Salem, Arash Firouzbakht, Jiann-Shiun Yuan:
MolData, a molecular benchmark for disease and target based machine learning. 10 - Damien E. Coupry
, Peter Pogány
:
Application of deep metric learning to molecular graph similarity. 11 - Chengyou Liu
, Andrew M. Hogan, Hunter Sturm, Mohd Wasif Khan, Md. Mohaiminul Islam, A. S. M. Zisanur Rahman
, Rebecca L. Davis, Silvia T. Cardona, Pingzhao Hu
:
Deep learning-driven prediction of drug mechanism of action from large-scale chemical-genetic interaction profiles. 12 - David Ferro-Costas
, Irea Mosquera-Lois
, Antonio Fernández-Ramos
:
Correction to: TorsiFlex: an automatic generator of torsional conformers. Application to the twenty proteinogenic amino acids. 13 - Junjie Wang, Naifeng Wen, Chunyu Wang
, Lingling Zhao, Liang Cheng:
ELECTRA-DTA: a new compound-protein binding affinity prediction model based on the contextualized sequence encoding. 14 - Min Htoo Lin, Zhengkai Tu, Connor W. Coley
:
Improving the performance of models for one-step retrosynthesis through re-ranking. 15 - Yimeng Wang, Yaxin Gu, Chaofeng Lou, Yuning Gong, Zengrui Wu, Weihua Li, Yun Tang, Guixia Liu
:
A multitask GNN-based interpretable model for discovery of selective JAK inhibitors. 16 - Melissa F. Adasme
, Sarah Naomi Bolz, Ali Al-Fatlawi, Michael Schroeder
:
Decomposing compounds enables reconstruction of interaction fingerprints for structure-based drug screening. 17 - Jiazhen He
, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum, Ola Engkvist:
Transformer-based molecular optimization beyond matched molecular pairs. 18 - Chong Lu, Shien Liu, Weihua Shi, Jun Yu, Zhou Zhou, Xiaoxiao Zhang, Xiaoli Lu, Faji Cai, Ning Xia, Yikai Wang
:
Systemic evolutionary chemical space exploration for drug discovery. 19 - Maxime Langevin, Rodolphe Vuilleumier, Marc Bianciotto
:
Explaining and avoiding failure modes in goal-directed generation of small molecules. 20 - Christina Humer
, Henry Heberle
, Floriane Montanari
, Thomas Wolf
, Florian Huber
, Ryan Henderson
, Julian Heinrich
, Marc Streit
:
ChemInformatics Model Explorer (CIME): exploratory analysis of chemical model explanations. 21 - Simon Bray
, Tim Dudgeon
, Rachael Skyner
, Rolf Backofen
, Björn A. Grüning
, Frank von Delft
:
Galaxy workflows for fragment-based virtual screening: a case study on the SARS-CoV-2 main protease. 22 - Ning-Ning Wang, Xiang-Gui Wang, Guo-Li Xiong
, Zi-Yi Yang, Ai-Ping Lu, Xiang Chen, Shao Liu, Tingjun Hou, Dong-Sheng Cao
:
Machine learning to predict metabolic drug interactions related to cytochrome P450 isozymes. 23 - Brendan D. McKay
, Mehmet Aziz Yirik
, Christoph Steinbeck
:
Surge: a fast open-source chemical graph generator. 24 - Barbara Zdrazil
, Rajarshi Guha:
Diversifying cheminformatics. 25 - Huanyu Tao, Qilong Wu, Xuejun Zhao, Peicong Lin, Sheng-You Huang
:
Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond. 26 - Doha Naga, Wolfgang Muster, Eunice Musvasva, Gerhard F. Ecker:
Off-targetP ML: an open source machine learning framework for off-target panel safety assessment of small molecules. 27 - Daniela Dolciami, Eloy D. Villasclaras-Fernández, Christos C. Kannas, Mirco Meniconi, Bissan Al-Lazikani, Albert A. Antolin:
canSAR chemistry registration and standardization pipeline. 28 - Diego Garay-Ruiz
, Carles Bo:
Chemical reaction network knowledge graphs: the OntoRXN ontology. 29 - Ruihan Zhang, Shoupeng Ren, Qi Dai, Tianze Shen, Xiaoli Li, Jin Li, Weilie Xiao
:
InflamNat: web-based database and predictor of anti-inflammatory natural products. 30 - Henning Otto Brinkhaus, Kohulan Rajan
, Achim Zielesny, Christoph Steinbeck
:
RanDepict: Random chemical structure depiction generator. 31 - Moritz Walter
, Luke N. Allen, Antonio de la Vega de León, Samuel J. Webb, Valerie J. Gillet:
Analysis of the benefits of imputation models over traditional QSAR models for toxicity prediction. 32 - Constantino A. García
, Alberto Gil-de-la-Fuente
, Coral Barbas, Abraham Otero:
Probabilistic metabolite annotation using retention time prediction and meta-learned projections. 33 - Barbara R. Terlouw, Sophie P. J. M. Vromans, Marnix H. Medema
:
PIKAChU: a Python-based informatics kit for analysing chemical units. 34 - Kedan He
:
Pharmacological affinity fingerprints derived from bioactivity data for the identification of designer drugs. 35 - Henning Otto Brinkhaus, Achim Zielesny, Christoph Steinbeck
, Kohulan Rajan
:
DECIMER - hand-drawn molecule images dataset. 36 - Barbara Füzi, Rahuman S. Malik-Sheriff, Emma J. Manners
, Henning Hermjakob
, Gerhard F. Ecker
:
KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study. 37 - Peter Willett:
Commentary: the first twelve years of the Journal of chemoinformatics. 38 - Bienfait Kabuyaya Isamura
, Kevin A. Lobb
:
AMADAR: a python-based package for large scale prediction of Diels-Alder transition state geometries and IRC path analysis. 39 - Maryam Abbasi
, Beatriz P. Santos, Tiago C. Pereira, Raul Sofia, Nelson R. C. Monteiro
, Carlos J. V. Simões, Rui M. M. Brito
, Bernardete Ribeiro, José Luís Oliveira
, Joel P. Arrais
:
Designing optimized drug candidates with Generative Adversarial Network. 40 - Zhanpeng Xu, Jianhua Li
, Zhaopeng Yang, Shiliang Li, Honglin Li:
SwinOCSR: end-to-end optical chemical structure recognition using a Swin Transformer. 41 - Kedan He
:
Correction to: Pharmacological affinity fingerprints derived from bioactivity data for the identification of designer drugs. 42 - Yifan Wang
, Jake Kalscheur, Elvis Ebikade, Qiang Li, Dionisios G. Vlachos:
LigninGraphs: lignin structure determination with multiscale graph modeling. 43 - Xiaochu Tong, Dingyan Wang, Xiaoyu Ding, Xiaoqin Tan, Qun Ren, Geng Chen, Yu Rong, Tingyang Xu
, Junzhou Huang
, Hualiang Jiang, Mingyue Zheng, Xutong Li
:
Blood-brain barrier penetration prediction enhanced by uncertainty estimation. 44 - Eitan Margulis
, Yuli Slavutsky, Tatjana Lang
, Maik Behrens, Yuval Benjamini, Masha Y. Niv:
BitterMatch: recommendation systems for matching molecules with bitter taste receptors. 45 - Mengting Huang, Chaofeng Lou, Zengrui Wu, Weihua Li, Philip W. Lee, Yun Tang, Guixia Liu:
In silico prediction of UGT-mediated metabolism in drug-like molecules via graph neural network. 46 - Akshai P. Sreenivasan
, Philip J. Harrison
, Wesley Schaal
, Damian J. Matuszewski, Kim Kultima
, Ola Spjuth
:
Predicting protein network topology clusters from chemical structure using deep learning. 47 - Neeraj Kumar
, Vishal Acharya
:
Machine intelligence-driven framework for optimized hit selection in virtual screening. 48 - Nina Lukashina
, Elena Kartysheva
, Ola Spjuth, Elizaveta Virko, Aleksei Shpilman:
SimVec: predicting polypharmacy side effects for new drugs. 49 - Jeremy R. Ash, Jacqueline M. Hughes-Oliver:
Confidence bands and hypothesis tests for hit enrichment curves. 50 - Norberto Sánchez-Cruz
, Emma Schymanski
:
Paths to Cheminformatics: Q&A with Norberto Sánchez-Cruz and Emma Schymanski. 51 - Yue Kong
, Xiaoman Zhao, Ruizi Liu, Zhenwu Yang, Hongyan Yin
, Bowen Zhao, Jinling Wang, Bingjie Qin, Aixia Yan
:
Integrating concept of pharmacophore with graph neural networks for chemical property prediction and interpretation. 52 - Maryam Abbasi
, Beatriz P. Santos, Tiago C. Pereira, Raul Sofa, Nelson R. C. Monteiro, Carlos J. V. Simões, Rui M. M. Brito, Bernardete Ribeiro, José Luís Oliveira, Joel P. Arrais:
Correction to: Designing optimized drug candidates with Generative Adversarial Network. 53 - Aljosa Smajic, Melanie Grandits
, Gerhard F. Ecker:
Using Jupyter Notebooks for re-training machine learning models. 54 - Olga A. Tarasova, Anastasia V. Rudik, Nadezhda Yu. Biziukova
, Dmitry Filimonov, Vladimir Poroikov:
Chemical named entity recognition in the texts of scientific publications using the naïve Bayes classifier approach. 55 - Yang Yu, Zhe Wang
, Lingling Wang, Sheng Tian
, Tingjun Hou, Huiyong Sun
:
Predicting the mutation effects of protein-ligand interactions via end-point binding free energy calculations: strategies and analyses. 56 - Jeaphianne P. M. van Rijn
, Antreas Afantitis
, Mustafa Culha
, Maria Dusinska
, Thomas E. Exner
, Nina Jeliazkova
, Eleonora Marta Longhin
, Iseult Lynch
, Georgia Melagraki
, Penny Nymark
, Anastasios G. Papadiamantis
, David A. Winkler
, Hulya Yilmaz
, Egon L. Willighagen
:
European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials. 57 - Yuri Kochnev, Jacob D. Durrant:
FPocketWeb: protein pocket hunting in a web browser. 58 - Rubaiyat Mohammad Khondaker, Stephen Gow
, Samantha Kanza
, Jeremy G. Frey
, Mahesan Niranjan:
Robustness under parameter and problem domain alterations of Bayesian optimization methods for chemical reactions. 59 - Xinqiao Wang, Chuansheng Yao, Yun Zhang, Jiahui Yu, Haoran Qiao, Chengyun Zhang, Yejian Wu, Renren Bai, Hongliang Duan
:
From theory to experiment: transformer-based generation enables rapid discovery of novel reactions. 60 - Fidan Musazade, Narmin Jamalova, Jamaladdin Hasanov:
Review of techniques and models used in optical chemical structure recognition in images and scanned documents. 61 - Milka Ljoncheva, Tomaz Stepisnik, Tina Kosjek
, Saso Dzeroski
:
Machine learning for identification of silylated derivatives from mass spectra. 62 - Stefan Müller
, Christoph Flamm
, Peter F. Stadler
:
What makes a reaction network "chemical"? 63 - Yasemin Yesiltepe, Niranjan Govind, Thomas O. Metz, Ryan S. Renslow
:
An initial investigation of accuracy required for the identification of small molecules in complex samples using quantum chemical calculated NMR chemical shifts. 64 - Mohamed-Amine Chadi, Hajar Mousannif, Ahmed Aamouche
:
Conditional reduction of the loss value versus reinforcement learning for biassing a de-novo drug design generator. 65 - Jan C. Brammer, Gerd Blanke, Claudia Kellner, Alexander Hoffmann, Sonja Herres-Pawlis, Ulrich Schatzschneider:
TUCAN: A molecular identifier and descriptor applicable to the whole periodic table from hydrogen to oganesson. 66 - Sangjin Ahn, Si Eun Lee
, Mi-Hyun Kim
:
Random-forest model for drug-target interaction prediction via Kullbeck-Leibler divergence. 67 - Morgan C. Thomas
, Noel M. O'Boyle, Andreas Bender, Chris de Graaf:
Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation. 68 - Ani Tevosyan, Lusine Khondkaryan, Hrant Khachatrian, Gohar Tadevosyan, Lilit Apresyan
, Nelly Babayan, Helga Stopper, Zaven Navoyan:
Improving VAE based molecular representations for compound property prediction. 69 - Jong Youl Choi, Pei Zhang, Kshitij Mehta, Andrew E. Blanchard, Massimiliano Lupo Pasini
:
Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules. 70 - Naifeng Wen, Guanqun Liu, Jie Zhang, Rubo Zhang, Yating Fu, Xu Han:
A fingerprints based molecular property prediction method using the BERT model. 71 - Louis Plyer
, Gilles Marcou
, Céline Perves, Rachel Schurhammer
, Alexandre Varnek:
Implementation of a soft grading system for chemistry in a Moodle plugin. 72 - António J. Preto, Paulo C. Correia, Irina S. Moreira
:
DrugTax: package for drug taxonomy identification and explainable feature extraction. 73 - Luca Chiesa
, Esther Kellenberger
:
One class classification for the detection of β2 adrenergic receptor agonists using single-ligand dynamic interaction data. 74 - Gaoang Wang, Jiahui Yu, Hongyan Du, Chao Shen, Xujun Zhang, Yifei Liu, Yangyang Zhang, Dong-Sheng Cao
, Peichen Pan
, Tingjun Hou:
VGSC-DB: an online database of voltage-gated sodium channels. 75 - Sangjin Ahn, Si Eun Lee, Mi-Hyun Kim
:
Correction : Random-forest model for drug-target interaction prediction via Kullback-Leibler divergence. 76 - Davide Bonanni, Luca Pinzi
, Giulio Rastelli:
Development of machine learning classifiers to predict compound activity on prostate cancer cell lines. 77 - Sherif Abdulkader Tawfik, Salvy P. Russo:
Naturally-meaningful and efficient descriptors: machine learning of material properties based on robust one-shot ab initio descriptors. 78 - Jonas Schaub
, Julian Zander
, Achim Zielesny
, Christoph Steinbeck
:
Scaffold Generator: a Java library implementing molecular scaffold functionalities in the Chemistry Development Kit (CDK). 79 - Davide Boldini, Lukas Friedrich, Daniel Kuhn, Stephan A. Sieber:
Tuning gradient boosting for imbalanced bioassay modelling with custom loss functions. 80 - Shenggeng Lin, Weizhi Chen, Gengwang Chen, Songchi Zhou, Dong-Qing Wei, Yi Xiong:
MDDI-SCL: predicting multi-type drug-drug interactions via supervised contrastive learning. 81 - Jürgen Bajorath, Ana L. Chávez-Hernández
, Miquel Duran-Frigola
, Eli Fernández-de Gortari, Johann Gasteiger, Edgar López-López, Gerald M. Maggiora, José L. Medina-Franco, Oscar Méndez-Lucio, Jordi Mestres, Ramón Alain Miranda-Quintana, Tudor I. Oprea, Fabien Plisson
, Fernando D. Prieto-Martínez, Raquel Rodríguez-Pérez, Paola Rondón-Villarreal, Fernanda I. Saldívar-González, Norberto Sánchez-Cruz, Marilia Valli:
Chemoinformatics and artificial intelligence colloquium: progress and challenges in developing bioactive compounds. 82 - Hwanhee Kim, Soohyun Ko, Byung Ju Kim, Sung Jin Ryu, Jaegyoon Ahn:
Predicting chemical structure using reinforcement learning with a stack-augmented conditional variational autoencoder. 83 - Mingyang Wang, Jike Wang, Gaoqi Weng, Yu Kang, Peichen Pan
, Dan Li, Yafeng Deng, Honglin Li, Chang-Yu Hsieh, Tingjun Hou:
ReMODE: a deep learning-based web server for target-specific drug design. 84 - Adelene Lai
, Jonas Schaub
, Christoph Steinbeck
, Emma Schymanski
:
An algorithm to classify homologous series within compound datasets. 85 - Iiris Sundin
, Alexey Voronov
, Haoping Xiao, Kostas Papadopoulos
, Esben Jannik Bjerrum, Markus Heinonen, Atanas Patronov, Samuel Kaski, Ola Engkvist:
Human-in-the-loop assisted de novo molecular design. 86 - Vincent F. Scalfani, Vishank D. Patel, Avery M. Fernandez:
Visualizing chemical space networks with RDKit and NetworkX. 87 - Xiaofan Zheng, Yoichi Tomiura, Kenshi Hayashi:
Investigation of the structure-odor relationship using a Transformer model. 88 - Liu-Xia Zhang, Jie Dong, Hui Wei, Shao-Hua Shi
, Ai-Ping Lu, Gui-Ming Deng, Dong-Sheng Cao
:
TCMSID: a simplified integrated database for drug discovery from traditional chinese medicine. 89
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