Journal of Cheminformatics

Papers
(The TQCC of Journal of Cheminformatics is 12. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-08-01 to 2025-08-01.)
ArticleCitations
Unexpected similarity between HIV-1 reverse transcriptase and tumor necrosis factor binding sites revealed by computer vision230
Predicting chemical structure using reinforcement learning with a stack-augmented conditional variational autoencoder108
Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for binding85
Moldina: a fast and accurate search algorithm for simultaneous docking of multiple ligands80
Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients77
Transformer-based molecular optimization beyond matched molecular pairs72
Explainable uncertainty quantifications for deep learning-based molecular property prediction66
Generating diversity and securing completeness in algorithmic retrosynthesis65
Assessing interaction recovery of predicted protein-ligand poses63
Equivariant diffusion for structure-based de novo ligand generation with latent-conditioning61
HERGAI: an artificial intelligence tool for structure-based prediction of hERG inhibitors57
European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials56
An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification54
Paths to cheminformatics: Q&A with Ann M. Richard53
Determining the parent and associated fragment formulae in mass spectrometry via the parent subformula graph51
VSFlow: an open-source ligand-based virtual screening tool49
PMF-CPI: assessing drug selectivity with a pretrained multi-functional model for compound–protein interactions49
Reproducible untargeted metabolomics workflow for exhaustive MS2 data acquisition of MS1 features49
Computer-aided pattern scoring (C@PS): a novel cheminformatic workflow to predict ligands with rare modes-of-action48
AutoTemplate: enhancing chemical reaction datasets for machine learning applications in organic chemistry45
APBIO: bioactive profiling of air pollutants through inferred bioactivity signatures and prediction of novel target interactions45
One chiral fingerprint to find them all44
Fifteen years of ChEMBL and its role in cheminformatics and drug discovery44
AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application43
ELECTRA-DTA: a new compound-protein binding affinity prediction model based on the contextualized sequence encoding41
MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data40
Advancements in thermochemical predictions: a multi-output thermodynamics-informed neural network approach39
Deep learning of multimodal networks with topological regularization for drug repositioning39
Explaining compound activity predictions with a substructure-aware loss for graph neural networks38
Implementation of an open chemistry knowledge base with a Semantic Wiki38
The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC–TOF MS metabolome samples37
Crossover operators for molecular graphs with an application to virtual drug screening37
NanoBinder: a machine learning assisted nanobody binding prediction tool using Rosetta energy scores36
Shinyscreen: mass spectrometry data inspection and quality checking utility34
Bitter peptide prediction using graph neural networks32
Splitting chemical structure data sets for federated privacy-preserving machine learning32
Analysis of the benefits of imputation models over traditional QSAR models for toxicity prediction32
Chemical toxicity prediction based on semi-supervised learning and graph convolutional neural network32
Semi-automated workflow for molecular pair analysis and QSAR-assisted transformation space expansion30
Accelerated hit identification with target evaluation, deep learning and automated labs: prospective validation in IRAK130
PyL3dMD: Python LAMMPS 3D molecular descriptors package30
canSAR chemistry registration and standardization pipeline30
The development of the generative adversarial supporting vector machine for molecular property generation29
Predictive modeling of visible-light azo-photoswitches’ properties using structural features28
CRAFT: a web-integrated cavity prediction tool based on flow transfer algorithm28
Exploration and augmentation of pharmacological space via adversarial auto-encoder model for facilitating kinase-centric drug development27
Enhancing chemical reaction search through contrastive representation learning and human-in-the-loop27
UMAP-based clustering split for rigorous evaluation of AI models for virtual screening on cancer cell lines*26
Structure-based machine learning screening identifies natural product candidates as potential geroprotectors26
Comprehensive benchmarking of computational tools for predicting toxicokinetic and physicochemical properties of chemicals26
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data25
Papyrus: a large-scale curated dataset aimed at bioactivity predictions25
New algorithms demonstrate untargeted detection of chemically meaningful changing units and formula assignment for HRMS data of polymeric mixtures in the open-source constellation web application25
GT-NMR: a novel graph transformer-based approach for accurate prediction of NMR chemical shifts25
Diversifying cheminformatics25
A systematic review of deep learning chemical language models in recent era25
Infrared spectrum analysis of organic molecules with neural networks using standard reference data sets in combination with real-world data24
ScaffoldGVAE: scaffold generation and hopping of drug molecules via a variational autoencoder based on multi-view graph neural networks24
Using test-time augmentation to investigate explainable AI: inconsistencies between method, model and human intuition24
PDBe CCDUtils: an RDKit-based toolkit for handling and analysing small molecules in the Protein Data Bank24
VGSC-DB: an online database of voltage-gated sodium channels23
Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices23
Scaffold Generator: a Java library implementing molecular scaffold functionalities in the Chemistry Development Kit (CDK)23
Implementation of a soft grading system for chemistry in a Moodle plugin22
Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond22
FlavorMiner: a machine learning platform for extracting molecular flavor profiles from structural data22
Visualising lead optimisation series using reduced graphs21
Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations21
Activity cliff-aware reinforcement learning for de novo drug design21
Notes on molecular fragmentation and parameter settings for a dissipative particle dynamics study of a C10E4/water mixture with lamellar bilayer formation21
Chemical reaction network knowledge graphs: the OntoRXN ontology21
Automatic molecular fragmentation by evolutionary optimisation21
Reaction rebalancing: a novel approach to curating reaction databases21
Chemical rules for optimization of chemical mutagenicity via matched molecular pairs analysis and machine learning methods20
Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty20
The specification game: rethinking the evaluation of drug response prediction for precision oncology20
DTi2Vec: Drug–target interaction prediction using network embedding and ensemble learning20
Application of deep metric learning to molecular graph similarity20
YoDe-Segmentation: automated noise-free retrieval of molecular structures from scientific publications20
Ilm-NMR-P31: an open-access 31P nuclear magnetic resonance database and data-driven prediction of 31P NMR shifts20
Towards a partial order graph for interactive pharmacophore exploration: extraction of pharmacophores activity delta19
A transformer based generative chemical language AI model for structural elucidation of organic compounds19
Data mining of PubChem bioassay records reveals diverse OXPHOS inhibitory chemotypes as potential therapeutic agents against ovarian cancer19
Learning protein-ligand binding affinity with atomic environment vectors19
AI-driven molecular generation of not-patented pharmaceutical compounds using world open patent data19
DeepSA: a deep-learning driven predictor of compound synthesis accessibility18
TCMSID: a simplified integrated database for drug discovery from traditional chinese medicine18
Achieving well-informed decision-making in drug discovery: a comprehensive calibration study using neural network-based structure-activity models18
Novel multi-objective affinity approach allows to identify pH-specific μ-opioid receptor agonists17
ChemInformatics Model Explorer (CIME): exploratory analysis of chemical model explanations17
Searching chemical databases in the pre-history of cheminformatics17
Off-targetP ML: an open source machine learning framework for off-target panel safety assessment of small molecules17
piscesCSM: prediction of anticancer synergistic drug combinations17
Deepmol: an automated machine and deep learning framework for computational chemistry17
HepatoToxicity Portal (HTP): an integrated database of drug-induced hepatotoxicity knowledgebase and graph neural network-based prediction model16
Enhancing molecular property prediction with quantized GNN models15
TB-IECS: an accurate machine learning-based scoring function for virtual screening15
Integrating synthetic accessibility with AI-based generative drug design15
Geometric deep learning for molecular property predictions with chemical accuracy across chemical space15
UnCorrupt SMILES: a novel approach to de novo design15
MolNexTR: a generalized deep learning model for molecular image recognition15
Leveraging computational tools to combat malaria: assessment and development of new therapeutics15
Machine learning to predict metabolic drug interactions related to cytochrome P450 isozymes15
Decrypting orphan GPCR drug discovery via multitask learning14
rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation14
The effect of noise on the predictive limit of QSAR models14
AI/ML methodologies and the future-will they be successful in designing the next generation of new chemical entities?14
QPHAR: quantitative pharmacophore activity relationship: method and validation14
One size does not fit all: revising traditional paradigms for assessing accuracy of QSAR models used for virtual screening14
What makes a reaction network “chemical”?14
Paths to cheminformatics: Q&A with Phyo Phyo Kyaw Zin14
DECIMER—hand-drawn molecule images dataset14
Tuning gradient boosting for imbalanced bioassay modelling with custom loss functions14
Human-in-the-loop active learning for goal-oriented molecule generation14
Automated molecular structure segmentation from documents using ChemSAM13
SMILES all around: structure to SMILES conversion for transition metal complexes13
Advancing material property prediction: using physics-informed machine learning models for viscosity13
A novel multitask learning algorithm for tasks with distinct chemical space: zebrafish toxicity prediction as an example13
Solvent flashcards: a visualisation tool for sustainable chemistry13
LAGNet: better electron density prediction for LCAO-based data and drug-like substances13
ReMODE: a deep learning-based web server for target-specific drug design13
PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping12
Application of machine reading comprehension techniques for named entity recognition in materials science12
qHTSWaterfall: 3-dimensional visualization software for quantitative high-throughput screening (qHTS) data12
Benchmarking ML in ADMET predictions: the practical impact of feature representations in ligand-based models12
How can SHAP values help to shape metabolic stability of chemical compounds?12
XSMILES: interactive visualization for molecules, SMILES and XAI attribution scores12
Ontologies4Cat: investigating the landscape of ontologies for catalysis research data management12
Llamol: a dynamic multi-conditional generative transformer for de novo molecular design12
OWSum: algorithmic odor prediction and insight into structure-odor relationships12
PIKAChU: a Python-based informatics kit for analysing chemical units12
Suitability of large language models for extraction of high-quality chemical reaction dataset from patent literature12
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