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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
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
LEADD: Lamarckian evolutionary algorithm for de novo drug design. 3 - Hadar Grimberg, Vinay S. Tiwari
Machine learning approaches to optimize small-molecule inhibitors for RNA targeting. 4 - Ingoo Lee
Sequence-based prediction of protein binding regions and drug-target interactions. 5 - Miao Yu
Reproducible untargeted metabolomics workflow for exhaustive MS2 data acquisition of MS1 features. 6 - Michael Freitas Gustavo
GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations. 7 - Ammar Ammar
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
MolData, a molecular benchmark for disease and target based machine learning. 10 - Damien E. Coupry
Application of deep metric learning to molecular graph similarity. 11 - Chengyou Liu
Deep learning-driven prediction of drug mechanism of action from large-scale chemical-genetic interaction profiles. 12 - David Ferro-Costas
Correction to: TorsiFlex: an automatic generator of torsional conformers. Application to the twenty proteinogenic amino acids. 13 - Junjie Wang, Naifeng Wen, Chunyu Wang
ELECTRA-DTA: a new compound-protein binding affinity prediction model based on the contextualized sequence encoding. 14 - Min Htoo Lin, Zhengkai Tu
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
Decomposing compounds enables reconstruction of interaction fingerprints for structure-based drug screening. 17 - Jiazhen He
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
ChemInformatics Model Explorer (CIME): exploratory analysis of chemical model explanations. 21 - Simon Bray
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
Machine learning to predict metabolic drug interactions related to cytochrome P450 isozymes. 23 - Brendan D. McKay
Surge: a fast open-source chemical graph generator. 24 - Barbara Zdrazil
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
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
RanDepict: Random chemical structure depiction generator. 31 - Moritz Walter
Analysis of the benefits of imputation models over traditional QSAR models for toxicity prediction. 32 - Constantino A. García
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
DECIMER - hand-drawn molecule images dataset. 36 - Barbara Füzi, Rahuman S. Malik-Sheriff, Emma J. Manners
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
AMADAR: a python-based package for large scale prediction of Diels-Alder transition state geometries and IRC path analysis. 39 - Maryam Abbasi
Designing optimized drug candidates with Generative Adversarial Network. 40 - Zhanpeng Xu, Jianhua 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
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
Blood-brain barrier penetration prediction enhanced by uncertainty estimation. 44 - Eitan Margulis
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
Predicting protein network topology clusters from chemical structure using deep learning. 47 - Neeraj Kumar
Machine intelligence-driven framework for optimized hit selection in virtual screening. 48 - Nina Lukashina
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
Paths to Cheminformatics: Q&A with Norberto Sánchez-Cruz and Emma Schymanski. 51 - Yue Kong
Integrating concept of pharmacophore with graph neural networks for chemical property prediction and interpretation. 52 - Maryam Abbasi
Correction to: Designing optimized drug candidates with Generative Adversarial Network. 53 - Aljosa Smajic, Melanie Grandits
Using Jupyter Notebooks for re-training machine learning models. 54 - Olga A. Tarasova, Anastasia V. Rudik, Nadezhda Yu. Biziukova
Chemical named entity recognition in the texts of scientific publications using the naïve Bayes classifier approach. 55 - Yang Yu, Zhe Wang
Predicting the mutation effects of protein-ligand interactions via end-point binding free energy calculations: strategies and analyses. 56 - Jeaphianne P. M. van Rijn
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
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
Machine learning for identification of silylated derivatives from mass spectra. 62 - Stefan Müller
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
Random-forest model for drug-target interaction prediction via Kullbeck-Leibler divergence. 67 - Morgan C. Thomas
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
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
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
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
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
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
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
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
ReMODE: a deep learning-based web server for target-specific drug design. 84 - Adelene Lai
An algorithm to classify homologous series within compound datasets. 85 - Iiris Sundin
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
TCMSID: a simplified integrated database for drug discovery from traditional chinese medicine. 89
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