Journal of Cheminformatics

Papers
(The TQCC of Journal of Cheminformatics is 11. 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 2021-06-01 to 2025-06-01.)
ArticleCitations
An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification383
Unexpected similarity between HIV-1 reverse transcriptase and tumor necrosis factor binding sites revealed by computer vision211
Predicting chemical structure using reinforcement learning with a stack-augmented conditional variational autoencoder96
Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for binding80
European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials75
Moldina: a fast and accurate search algorithm for simultaneous docking of multiple ligands69
Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients59
Generating diversity and securing completeness in algorithmic retrosynthesis58
Transformer-based molecular optimization beyond matched molecular pairs55
Assessing interaction recovery of predicted protein-ligand poses54
Explainable uncertainty quantifications for deep learning-based molecular property prediction51
Determining the parent and associated fragment formulae in mass spectrometry via the parent subformula graph50
Paths to cheminformatics: Q&A with Ann M. Richard50
Equivariant diffusion for structure-based de novo ligand generation with latent-conditioning50
Deep learning of multimodal networks with topological regularization for drug repositioning48
VSFlow: an open-source ligand-based virtual screening tool48
APBIO: bioactive profiling of air pollutants through inferred bioactivity signatures and prediction of novel target interactions47
Reproducible untargeted metabolomics workflow for exhaustive MS2 data acquisition of MS1 features47
MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data44
Computer-aided pattern scoring (C@PS): a novel cheminformatic workflow to predict ligands with rare modes-of-action43
One chiral fingerprint to find them all41
AutoTemplate: enhancing chemical reaction datasets for machine learning applications in organic chemistry41
PMF-CPI: assessing drug selectivity with a pretrained multi-functional model for compound–protein interactions40
Fifteen years of ChEMBL and its role in cheminformatics and drug discovery39
AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application39
ELECTRA-DTA: a new compound-protein binding affinity prediction model based on the contextualized sequence encoding39
Analysis of the benefits of imputation models over traditional QSAR models for toxicity prediction37
Bitter peptide prediction using graph neural networks37
Splitting chemical structure data sets for federated privacy-preserving machine learning35
Explaining compound activity predictions with a substructure-aware loss for graph neural networks35
The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC–TOF MS metabolome samples35
Chemical toxicity prediction based on semi-supervised learning and graph convolutional neural network34
PyL3dMD: Python LAMMPS 3D molecular descriptors package33
Semi-automated workflow for molecular pair analysis and QSAR-assisted transformation space expansion32
canSAR chemistry registration and standardization pipeline31
Comprehensive benchmarking of computational tools for predicting toxicokinetic and physicochemical properties of chemicals30
CRAFT: a web-integrated cavity prediction tool based on flow transfer algorithm29
Accelerated hit identification with target evaluation, deep learning and automated labs: prospective validation in IRAK129
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data28
Exploration and augmentation of pharmacological space via adversarial auto-encoder model for facilitating kinase-centric drug development28
Predictive modeling of visible-light azo-photoswitches’ properties using structural features28
Enhancing chemical reaction search through contrastive representation learning and human-in-the-loop28
GT-NMR: a novel graph transformer-based approach for accurate prediction of NMR chemical shifts27
Papyrus: a large-scale curated dataset aimed at bioactivity predictions26
A systematic review of deep learning chemical language models in recent era25
Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices24
Diversifying cheminformatics24
Infrared spectrum analysis of organic molecules with neural networks using standard reference data sets in combination with real-world data24
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 application24
FlavorMiner: a machine learning platform for extracting molecular flavor profiles from structural data23
Scaffold Generator: a Java library implementing molecular scaffold functionalities in the Chemistry Development Kit (CDK)23
PDBe CCDUtils: an RDKit-based toolkit for handling and analysing small molecules in the Protein Data Bank23
VGSC-DB: an online database of voltage-gated sodium channels23
Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond22
ScaffoldGVAE: scaffold generation and hopping of drug molecules via a variational autoencoder based on multi-view graph neural networks22
Using test-time augmentation to investigate explainable AI: inconsistencies between method, model and human intuition22
LigTMap: ligand and structure-based target identification and activity prediction for small molecular compounds22
Implementation of a soft grading system for chemistry in a Moodle plugin22
YoDe-Segmentation: automated noise-free retrieval of molecular structures from scientific publications21
Automatic molecular fragmentation by evolutionary optimisation21
Notes on molecular fragmentation and parameter settings for a dissipative particle dynamics study of a C10E4/water mixture with lamellar bilayer formation21
Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations21
Reaction rebalancing: a novel approach to curating reaction databases21
The specification game: rethinking the evaluation of drug response prediction for precision oncology20
Visualising lead optimisation series using reduced graphs20
Application of deep metric learning to molecular graph similarity20
Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty20
Activity cliff-aware reinforcement learning for de novo drug design20
Ilm-NMR-P31: an open-access 31P nuclear magnetic resonance database and data-driven prediction of 31P NMR shifts20
DTi2Vec: Drug–target interaction prediction using network embedding and ensemble learning20
Chemical reaction network knowledge graphs: the OntoRXN ontology20
AI-driven molecular generation of not-patented pharmaceutical compounds using world open patent data19
Achieving well-informed decision-making in drug discovery: a comprehensive calibration study using neural network-based structure-activity models19
Novel multi-objective affinity approach allows to identify pH-specific μ-opioid receptor agonists19
Chemical rules for optimization of chemical mutagenicity via matched molecular pairs analysis and machine learning methods19
Towards a partial order graph for interactive pharmacophore exploration: extraction of pharmacophores activity delta19
Deepmol: an automated machine and deep learning framework for computational chemistry18
ChemInformatics Model Explorer (CIME): exploratory analysis of chemical model explanations18
Learning protein-ligand binding affinity with atomic environment vectors18
TCMSID: a simplified integrated database for drug discovery from traditional chinese medicine18
Data mining of PubChem bioassay records reveals diverse OXPHOS inhibitory chemotypes as potential therapeutic agents against ovarian cancer18
Off-targetP ML: an open source machine learning framework for off-target panel safety assessment of small molecules18
DeepSA: a deep-learning driven predictor of compound synthesis accessibility18
Machine learning to predict metabolic drug interactions related to cytochrome P450 isozymes17
Ensemble completeness in conformer sampling: the case of small macrocycles17
Searching chemical databases in the pre-history of cheminformatics17
piscesCSM: prediction of anticancer synergistic drug combinations17
Enhancing molecular property prediction with quantized GNN models16
AI/ML methodologies and the future-will they be successful in designing the next generation of new chemical entities?16
MolNexTR: a generalized deep learning model for molecular image recognition16
HepatoToxicity Portal (HTP): an integrated database of drug-induced hepatotoxicity knowledgebase and graph neural network-based prediction model16
Paths to cheminformatics: Q&A with Phyo Phyo Kyaw Zin15
TB-IECS: an accurate machine learning-based scoring function for virtual screening15
What makes a reaction network “chemical”?15
UnCorrupt SMILES: a novel approach to de novo design15
Integrating synthetic accessibility with AI-based generative drug design15
Nonadditivity in public and inhouse data: implications for drug design15
Geometric deep learning for molecular property predictions with chemical accuracy across chemical space15
Leveraging computational tools to combat malaria: assessment and development of new therapeutics15
QPHAR: quantitative pharmacophore activity relationship: method and validation14
rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation14
Human-in-the-loop active learning for goal-oriented molecule generation14
Decrypting orphan GPCR drug discovery via multitask learning14
Tuning gradient boosting for imbalanced bioassay modelling with custom loss functions14
One size does not fit all: revising traditional paradigms for assessing accuracy of QSAR models used for virtual screening13
The effect of noise on the predictive limit of QSAR models13
Advancing material property prediction: using physics-informed machine learning models for viscosity13
Automated molecular structure segmentation from documents using ChemSAM13
DECIMER—hand-drawn molecule images dataset13
Llamol: a dynamic multi-conditional generative transformer for de novo molecular design12
SMILES all around: structure to SMILES conversion for transition metal complexes12
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
Evaluating uncertainty-based active learning for accelerating the generalization of molecular property prediction12
Solvent flashcards: a visualisation tool for sustainable chemistry12
ReMODE: a deep learning-based web server for target-specific drug design12
XSMILES: interactive visualization for molecules, SMILES and XAI attribution scores12
Ontologies4Cat: investigating the landscape of ontologies for catalysis research data management12
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
LAGNet: better electron density prediction for LCAO-based data and drug-like substances12
A novel multitask learning algorithm for tasks with distinct chemical space: zebrafish toxicity prediction as an example12
How can SHAP values help to shape metabolic stability of chemical compounds?12
Pretraining graph transformers with atom-in-a-molecule quantum properties for improved ADMET modeling12
Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors11
Galaxy workflows for fragment-based virtual screening: a case study on the SARS-CoV-2 main protease11
Machine learning approaches to optimize small-molecule inhibitors for RNA targeting11
From papers to RDF-based integration of physicochemical data and adverse outcome pathways for nanomaterials11
DrugDiff: small molecule diffusion model with flexible guidance towards molecular properties11
Building shape-focused pharmacophore models for effective docking screening11
PromptSMILES: prompting for scaffold decoration and fragment linking in chemical language models11
MDDI-SCL: predicting multi-type drug-drug interactions via supervised contrastive learning11
Chemical characteristics vectors map the chemical space of natural biomes from untargeted mass spectrometry data11
InterDILI: interpretable prediction of drug-induced liver injury through permutation feature importance and attention mechanism11
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