Journal of Cheminformatics

Papers
(The TQCC of Journal of Cheminformatics is 14. 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 2022-05-01 to 2026-05-01.)
ArticleCitations
Evolve with your research: stepwise system evolution from document-driven to fact-centric research data management in materials science216
Assessing interaction recovery of predicted protein-ligand poses117
Predicting chemical structure using reinforcement learning with a stack-augmented conditional variational autoencoder113
Explainable uncertainty quantifications for deep learning-based molecular property prediction90
Moldina: a fast and accurate search algorithm for simultaneous docking of multiple ligands89
Equivariant diffusion for structure-based de novo ligand generation with latent-conditioning89
ANNalog: generation of MedChem-similar molecules84
Generating diversity and securing completeness in algorithmic retrosynthesis74
European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials68
HERGAI: an artificial intelligence tool for structure-based prediction of hERG inhibitors68
Biosynfoni: a biosynthesis-informed and interpretable lightweight molecular fingerprint63
Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients60
An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification60
Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for binding60
Determining the parent and associated fragment formulae in mass spectrometry via the parent subformula graph56
Privileged structure-based molecular fingerprints for organic electronic materials: towards intuitive machine learning interpretation55
Paths to cheminformatics: Q&A with Ann M. Richard51
Deep learning of multimodal networks with topological regularization for drug repositioning49
APBIO: bioactive profiling of air pollutants through inferred bioactivity signatures and prediction of novel target interactions48
PMF-CPI: assessing drug selectivity with a pretrained multi-functional model for compound–protein interactions47
AdapTor: Adaptive Topological Regression for quantitative structure–activity relationship modeling47
MolPrice: assessing synthetic accessibility of molecules based on market value47
MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data46
AutoTemplate: enhancing chemical reaction datasets for machine learning applications in organic chemistry45
Novel molecule design with POWGAN, a policy-optimized Wasserstein generative adversarial network44
VSFlow: an open-source ligand-based virtual screening tool42
Machine learning to predict food effects during drug development: a comprehensive review41
Computer-aided pattern scoring (C@PS): a novel cheminformatic workflow to predict ligands with rare modes-of-action41
AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application41
NPBS Atlas: a comprehensive data resource for exploring the biological sources of natural products40
Fifteen years of ChEMBL and its role in cheminformatics and drug discovery40
Analysis of the benefits of imputation models over traditional QSAR models for toxicity prediction39
One chiral fingerprint to find them all39
A quantum chemical dataset of interacting molecular pairs for chemical reaction studies38
Implementation of an open chemistry knowledge base with a Semantic Wiki37
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
Explaining compound activity predictions with a substructure-aware loss for graph neural networks36
Shinyscreen: mass spectrometry data inspection and quality checking utility36
The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC–TOF MS metabolome samples35
Advancements in thermochemical predictions: a multi-output thermodynamics-informed neural network approach35
Collision-free morgan fingerprints: a principled approach to enhance machine learning performance and interpretability in chemistry34
Bitter peptide prediction using graph neural networks34
Enhancing chemical reaction search through contrastive representation learning and human-in-the-loop33
ProjFusNet: deep neural network for peptide precursor prediction using projection-fused protein language model and structural features33
Prediction model for chemical explosion consequences via multimodal feature fusion33
PyL3dMD: Python LAMMPS 3D molecular descriptors package32
PURE: policy-guided unbiased REpresentations for structure-constrained molecular generation32
Accurate structure-activity relationship prediction of antioxidant peptides using a multimodal deep learning framework31
Ionization efficiency prediction of electrospray ionization mass spectrometry analytes based on molecular fingerprints and cumulative neutral losses31
Summarizing relationships between chemicals, genes, proteins, and diseases in PubChem using analysis of their co-occurrences in patents31
Accelerated hit identification with target evaluation, deep learning and automated labs: prospective validation in IRAK130
Structure-based machine learning screening identifies natural product candidates as potential geroprotectors30
GT-NMR: a novel graph transformer-based approach for accurate prediction of NMR chemical shifts30
The development of the generative adversarial supporting vector machine for molecular property generation30
A comprehensive evaluation of advanced methods for identifying structural alerts using extensive toxicity data28
Predictive modeling of visible-light azo-photoswitches’ properties using structural features28
Comprehensive benchmarking of computational tools for predicting toxicokinetic and physicochemical properties of chemicals28
CRAFT: a web-integrated cavity prediction tool based on flow transfer algorithm28
How quantum-chemical geometry optimization level affects classical 3D descriptors and QSAR performance: a comparative study28
ProQSAR: A modular and reproducible framework for small-data QSAR modeling with fit-and-use models27
UMAP-based clustering split for rigorous evaluation of AI models for virtual screening on cancer cell lines*27
A systematic review of deep learning chemical language models in recent era27
Using test-time augmentation to investigate explainable AI: inconsistencies between method, model and human intuition26
canSAR chemistry registration and standardization pipeline26
Scaffold Generator: a Java library implementing molecular scaffold functionalities in the Chemistry Development Kit (CDK)26
Papyrus: a large-scale curated dataset aimed at bioactivity predictions26
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 application26
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data26
VGSC-DB: an online database of voltage-gated sodium channels25
ScaffoldGVAE: scaffold generation and hopping of drug molecules via a variational autoencoder based on multi-view graph neural networks24
Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond24
Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices24
PDBe CCDUtils: an RDKit-based toolkit for handling and analysing small molecules in the Protein Data Bank23
FlavorMiner: a machine learning platform for extracting molecular flavor profiles from structural data23
Infrared spectrum analysis of organic molecules with neural networks using standard reference data sets in combination with real-world data23
Gromacs MetaDump: a tool for extracting GROMACS simulation metadata23
Notes on molecular fragmentation and parameter settings for a dissipative particle dynamics study of a C10E4/water mixture with lamellar bilayer formation22
Ilm-NMR-P31: an open-access 31P nuclear magnetic resonance database and data-driven prediction of 31P NMR shifts22
Chemical reaction network knowledge graphs: the OntoRXN ontology22
How to crack a SMILES: automatic crosschecked chemical structure resolution across multiple services using MoleculeResolver22
Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations22
AI-powered prediction of critical properties and boiling points: a hybrid ensemble learning and QSPR approach22
Implementation of a soft grading system for chemistry in a Moodle plugin22
Visualising lead optimisation series using reduced graphs22
Subgrapher: visual fingerprinting of chemical structures22
Automatic molecular fragmentation by evolutionary optimisation21
Activity cliff-aware reinforcement learning for de novo drug design21
The specification game: rethinking the evaluation of drug response prediction for precision oncology21
YoDe-Segmentation: automated noise-free retrieval of molecular structures from scientific publications21
Reaction rebalancing: a novel approach to curating reaction databases21
Novel multi-objective affinity approach allows to identify pH-specific μ-opioid receptor agonists20
Data mining of PubChem bioassay records reveals diverse OXPHOS inhibitory chemotypes as potential therapeutic agents against ovarian cancer20
Achieving well-informed decision-making in drug discovery: a comprehensive calibration study using neural network-based structure-activity models20
Deepmol: an automated machine and deep learning framework for computational chemistry20
Off-targetP ML: an open source machine learning framework for off-target panel safety assessment of small molecules19
TCMSID: a simplified integrated database for drug discovery from traditional chinese medicine19
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 compounds18
Integrating synthetic accessibility with AI-based generative drug design18
Chemical rules for optimization of chemical mutagenicity via matched molecular pairs analysis and machine learning methods18
SPARFlow: a KNIME workflow for integrated structure–activity or structure–property relationship analysis18
Enhancing molecular property prediction with quantized GNN models18
Geometric deep learning for molecular property predictions with chemical accuracy across chemical space18
AI-driven molecular generation of not-patented pharmaceutical compounds using world open patent data18
Searching chemical databases in the pre-history of cheminformatics18
Leveraging computational tools to combat malaria: assessment and development of new therapeutics18
DeepSA: a deep-learning driven predictor of compound synthesis accessibility18
AI/ML methodologies and the future-will they be successful in designing the next generation of new chemical entities?17
piscesCSM: prediction of anticancer synergistic drug combinations17
Multiscale analysis and optimal glioma therapeutic candidate discovery using the CANDO platform17
MolNexTR: a generalized deep learning model for molecular image recognition17
Correction: Enhanced Thompson sampling by roulette wheel selection for screening ultralarge combinatorial libraries17
Torsion angular bin strings: algorithmic update and additional validation17
TB-IECS: an accurate machine learning-based scoring function for virtual screening17
Multimodal graph fusion with statistically guided parsimonious descriptor selection for molecular property prediction17
HepatoToxicity Portal (HTP): an integrated database of drug-induced hepatotoxicity knowledgebase and graph neural network-based prediction model17
Systematic benchmarking of 13 AI methods for predicting cyclic peptide membrane permeability17
Nanodesigner: resolving the complex-CDR interdependency with iterative refinement16
Decrypting orphan GPCR drug discovery via multitask learning16
DECIMER—hand-drawn molecule images dataset16
Human-in-the-loop active learning for goal-oriented molecule generation16
Tuning gradient boosting for imbalanced bioassay modelling with custom loss functions16
UnCorrupt SMILES: a novel approach to de novo design16
What makes a reaction network “chemical”?16
One size does not fit all: revising traditional paradigms for assessing accuracy of QSAR models used for virtual screening16
RGReco: a unified framework for automated R-group recognition in chemical publications16
rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation16
Paths to cheminformatics: Q&A with Phyo Phyo Kyaw Zin16
Contrastive representation learning and capsule networks enable accurate identification of ferroptosis-related proteins16
VitroBert: modeling DILI by pretraining BERT on in vitro data16
Advancing material property prediction: using physics-informed machine learning models for viscosity16
Benchmarking ML in ADMET predictions: the practical impact of feature representations in ligand-based models15
A novel multitask learning algorithm for tasks with distinct chemical space: zebrafish toxicity prediction as an example15
Correction: Advancements in thermochemical predictions: a multi-output thermodynamics-informed neural network approach15
Automated molecular structure segmentation from documents using ChemSAM15
Llamol: a dynamic multi-conditional generative transformer for de novo molecular design15
LAGNet: better electron density prediction for LCAO-based data and drug-like substances15
ReMODE: a deep learning-based web server for target-specific drug design15
qHTSWaterfall: 3-dimensional visualization software for quantitative high-throughput screening (qHTS) data15
XSMILES: interactive visualization for molecules, SMILES and XAI attribution scores15
Ontologies4Cat: investigating the landscape of ontologies for catalysis research data management15
Prediction of UGT-mediated phase II metabolism via ligand- and structure-based predictive models15
PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping15
Solvent flashcards: a visualisation tool for sustainable chemistry15
Nipah Virus Inhibitor Knowledgebase (NVIK): a combined evidence approach to prioritise small molecule inhibitors14
VNFlow: integration of variational autoencoders and normalizing flows for novel molecular design14
Evaluating uncertainty-based active learning for accelerating the generalization of molecular property prediction14
PIKAChU: a Python-based informatics kit for analysing chemical units14
Suitability of large language models for extraction of high-quality chemical reaction dataset from patent literature14
SMILES all around: structure to SMILES conversion for transition metal complexes14
OWSum: algorithmic odor prediction and insight into structure-odor relationships14
Application of machine reading comprehension techniques for named entity recognition in materials science14
Predicting the critical micelle concentration of binary surfactant mixtures using machine learning14
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