Journal of Cheminformatics

Article	Citations
Evolve with your research: stepwise system evolution from document-driven to fact-centric research data management in materials science	216
Assessing interaction recovery of predicted protein-ligand poses	117
Predicting chemical structure using reinforcement learning with a stack-augmented conditional variational autoencoder	113
Explainable uncertainty quantifications for deep learning-based molecular property prediction	90
Moldina: a fast and accurate search algorithm for simultaneous docking of multiple ligands	89
Equivariant diffusion for structure-based de novo ligand generation with latent-conditioning	89
ANNalog: generation of MedChem-similar molecules	84
Generating diversity and securing completeness in algorithmic retrosynthesis	74
European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials	68
HERGAI: an artificial intelligence tool for structure-based prediction of hERG inhibitors	68
Biosynfoni: a biosynthesis-informed and interpretable lightweight molecular fingerprint	63
An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification	60
Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for binding	60
Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients	60
Determining the parent and associated fragment formulae in mass spectrometry via the parent subformula graph	56
Privileged structure-based molecular fingerprints for organic electronic materials: towards intuitive machine learning interpretation	55
Paths to cheminformatics: Q&A with Ann M. Richard	51
Deep learning of multimodal networks with topological regularization for drug repositioning	49
APBIO: bioactive profiling of air pollutants through inferred bioactivity signatures and prediction of novel target interactions	48
AdapTor: Adaptive Topological Regression for quantitative structure–activity relationship modeling	47
MolPrice: assessing synthetic accessibility of molecules based on market value	47
PMF-CPI: assessing drug selectivity with a pretrained multi-functional model for compound–protein interactions	47
MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data	46
AutoTemplate: enhancing chemical reaction datasets for machine learning applications in organic chemistry	45
Novel molecule design with POWGAN, a policy-optimized Wasserstein generative adversarial network	44

VSFlow: an open-source ligand-based virtual screening tool	42
Computer-aided pattern scoring (C@PS): a novel cheminformatic workflow to predict ligands with rare modes-of-action	41
AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application	41
Machine learning to predict food effects during drug development: a comprehensive review	41
NPBS Atlas: a comprehensive data resource for exploring the biological sources of natural products	40
Fifteen years of ChEMBL and its role in cheminformatics and drug discovery	40
Analysis of the benefits of imputation models over traditional QSAR models for toxicity prediction	39
One chiral fingerprint to find them all	39
A quantum chemical dataset of interacting molecular pairs for chemical reaction studies	38
Implementation of an open chemistry knowledge base with a Semantic Wiki	37
Crossover operators for molecular graphs with an application to virtual drug screening	37
NanoBinder: a machine learning assisted nanobody binding prediction tool using Rosetta energy scores	36
Explaining compound activity predictions with a substructure-aware loss for graph neural networks	36
Shinyscreen: mass spectrometry data inspection and quality checking utility	36
The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC–TOF MS metabolome samples	35
Advancements in thermochemical predictions: a multi-output thermodynamics-informed neural network approach	35
Collision-free morgan fingerprints: a principled approach to enhance machine learning performance and interpretability in chemistry	34
Bitter peptide prediction using graph neural networks	34
ProjFusNet: deep neural network for peptide precursor prediction using projection-fused protein language model and structural features	33
Prediction model for chemical explosion consequences via multimodal feature fusion	33
Enhancing chemical reaction search through contrastive representation learning and human-in-the-loop	33
PyL3dMD: Python LAMMPS 3D molecular descriptors package	32
PURE: policy-guided unbiased REpresentations for structure-constrained molecular generation	32
Ionization efficiency prediction of electrospray ionization mass spectrometry analytes based on molecular fingerprints and cumulative neutral losses	31
Summarizing relationships between chemicals, genes, proteins, and diseases in PubChem using analysis of their co-occurrences in patents	31
Accurate structure-activity relationship prediction of antioxidant peptides using a multimodal deep learning framework	31
GT-NMR: a novel graph transformer-based approach for accurate prediction of NMR chemical shifts	30
The development of the generative adversarial supporting vector machine for molecular property generation	30
Accelerated hit identification with target evaluation, deep learning and automated labs: prospective validation in IRAK1	30
Structure-based machine learning screening identifies natural product candidates as potential geroprotectors	30
Predictive modeling of visible-light azo-photoswitches’ properties using structural features	28
Comprehensive benchmarking of computational tools for predicting toxicokinetic and physicochemical properties of chemicals	28
CRAFT: a web-integrated cavity prediction tool based on flow transfer algorithm	28
How quantum-chemical geometry optimization level affects classical 3D descriptors and QSAR performance: a comparative study	28
A comprehensive evaluation of advanced methods for identifying structural alerts using extensive toxicity data	28
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 era	27
ProQSAR: A modular and reproducible framework for small-data QSAR modeling with fit-and-use models	27
Using test-time augmentation to investigate explainable AI: inconsistencies between method, model and human intuition	26
canSAR chemistry registration and standardization pipeline	26
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 predictions	26
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 application	26
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data	26
VGSC-DB: an online database of voltage-gated sodium channels	25
ScaffoldGVAE: scaffold generation and hopping of drug molecules via a variational autoencoder based on multi-view graph neural networks	24
Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond	24
Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices	24
PDBe CCDUtils: an RDKit-based toolkit for handling and analysing small molecules in the Protein Data Bank	23
FlavorMiner: a machine learning platform for extracting molecular flavor profiles from structural data	23

Infrared spectrum analysis of organic molecules with neural networks using standard reference data sets in combination with real-world data	23
Gromacs MetaDump: a tool for extracting GROMACS simulation metadata	23
How to crack a SMILES: automatic crosschecked chemical structure resolution across multiple services using MoleculeResolver	22
Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations	22
AI-powered prediction of critical properties and boiling points: a hybrid ensemble learning and QSPR approach	22
Implementation of a soft grading system for chemistry in a Moodle plugin	22
Visualising lead optimisation series using reduced graphs	22
Subgrapher: visual fingerprinting of chemical structures	22
Notes on molecular fragmentation and parameter settings for a dissipative particle dynamics study of a C10E4/water mixture with lamellar bilayer formation	22
Ilm-NMR-P31: an open-access 31P nuclear magnetic resonance database and data-driven prediction of 31P NMR shifts	22
Chemical reaction network knowledge graphs: the OntoRXN ontology	22
Reaction rebalancing: a novel approach to curating reaction databases	21
Activity cliff-aware reinforcement learning for de novo drug design	21
YoDe-Segmentation: automated noise-free retrieval of molecular structures from scientific publications	21
The specification game: rethinking the evaluation of drug response prediction for precision oncology	21
Automatic molecular fragmentation by evolutionary optimisation	21
Achieving well-informed decision-making in drug discovery: a comprehensive calibration study using neural network-based structure-activity models	20
Deepmol: an automated machine and deep learning framework for computational chemistry	20
Novel multi-objective affinity approach allows to identify pH-specific μ-opioid receptor agonists	20
Data mining of PubChem bioassay records reveals diverse OXPHOS inhibitory chemotypes as potential therapeutic agents against ovarian cancer	20
Towards a partial order graph for interactive pharmacophore exploration: extraction of pharmacophores activity delta	19
Off-targetP ML: an open source machine learning framework for off-target panel safety assessment of small molecules	19
TCMSID: a simplified integrated database for drug discovery from traditional chinese medicine	19
Leveraging computational tools to combat malaria: assessment and development of new therapeutics	18
DeepSA: a deep-learning driven predictor of compound synthesis accessibility	18
A transformer based generative chemical language AI model for structural elucidation of organic compounds	18
Integrating synthetic accessibility with AI-based generative drug design	18
Chemical rules for optimization of chemical mutagenicity via matched molecular pairs analysis and machine learning methods	18
SPARFlow: a KNIME workflow for integrated structure–activity or structure–property relationship analysis	18
Enhancing molecular property prediction with quantized GNN models	18
Geometric deep learning for molecular property predictions with chemical accuracy across chemical space	18
AI-driven molecular generation of not-patented pharmaceutical compounds using world open patent data	18
Searching chemical databases in the pre-history of cheminformatics	18
TB-IECS: an accurate machine learning-based scoring function for virtual screening	17
Multimodal graph fusion with statistically guided parsimonious descriptor selection for molecular property prediction	17
HepatoToxicity Portal (HTP): an integrated database of drug-induced hepatotoxicity knowledgebase and graph neural network-based prediction model	17
Systematic benchmarking of 13 AI methods for predicting cyclic peptide membrane permeability	17
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 combinations	17
Multiscale analysis and optimal glioma therapeutic candidate discovery using the CANDO platform	17
MolNexTR: a generalized deep learning model for molecular image recognition	17
Correction: Enhanced Thompson sampling by roulette wheel selection for screening ultralarge combinatorial libraries	17
Torsion angular bin strings: algorithmic update and additional validation	17
Paths to cheminformatics: Q&A with Phyo Phyo Kyaw Zin	16
Contrastive representation learning and capsule networks enable accurate identification of ferroptosis-related proteins	16
VitroBert: modeling DILI by pretraining BERT on in vitro data	16
Advancing material property prediction: using physics-informed machine learning models for viscosity	16
Nanodesigner: resolving the complex-CDR interdependency with iterative refinement	16
Decrypting orphan GPCR drug discovery via multitask learning	16
DECIMER—hand-drawn molecule images dataset	16
Human-in-the-loop active learning for goal-oriented molecule generation	16
Tuning gradient boosting for imbalanced bioassay modelling with custom loss functions	16
UnCorrupt SMILES: a novel approach to de novo design	16
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 screening	16
RGReco: a unified framework for automated R-group recognition in chemical publications	16
rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation	16
Ontologies4Cat: investigating the landscape of ontologies for catalysis research data management	15
Prediction of UGT-mediated phase II metabolism via ligand- and structure-based predictive models	15
PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping	15
Solvent flashcards: a visualisation tool for sustainable chemistry	15
Benchmarking ML in ADMET predictions: the practical impact of feature representations in ligand-based models	15
A novel multitask learning algorithm for tasks with distinct chemical space: zebrafish toxicity prediction as an example	15
Correction: Advancements in thermochemical predictions: a multi-output thermodynamics-informed neural network approach	15
Automated molecular structure segmentation from documents using ChemSAM	15
Llamol: a dynamic multi-conditional generative transformer for de novo molecular design	15
LAGNet: better electron density prediction for LCAO-based data and drug-like substances	15
ReMODE: a deep learning-based web server for target-specific drug design	15
qHTSWaterfall: 3-dimensional visualization software for quantitative high-throughput screening (qHTS) data	15
XSMILES: interactive visualization for molecules, SMILES and XAI attribution scores	15
OWSum: algorithmic odor prediction and insight into structure-odor relationships	14
Application of machine reading comprehension techniques for named entity recognition in materials science	14
Predicting the critical micelle concentration of binary surfactant mixtures using machine learning	14
Nipah Virus Inhibitor Knowledgebase (NVIK): a combined evidence approach to prioritise small molecule inhibitors	14
VNFlow: integration of variational autoencoders and normalizing flows for novel molecular design	14
Evaluating uncertainty-based active learning for accelerating the generalization of molecular property prediction	14
PIKAChU: a Python-based informatics kit for analysing chemical units	14
Suitability of large language models for extraction of high-quality chemical reaction dataset from patent literature	14
SMILES all around: structure to SMILES conversion for transition metal complexes	14
From papers to RDF-based integration of physicochemical data and adverse outcome pathways for nanomaterials	13

PKSmart: an open-source computational model to predict intravenous pharmacokinetics of small molecules	13
Uncovering molecular determinants of potency and binding affinity in hit compounds targeting FGF14/Nav1.6 complex	13
Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors	13
Evaluation of chirality descriptors derived from SMILES heteroencoders	13
Capsule graph networks for accurate and interpretable crystalline materials property prediction	13
InterDILI: interpretable prediction of drug-induced liver injury through permutation feature importance and attention mechanism	13
Chemical characteristics vectors map the chemical space of natural biomes from untargeted mass spectrometry data	13
PromptSMILES: prompting for scaffold decoration and fragment linking in chemical language models	13
Pretraining graph transformers with atom-in-a-molecule quantum properties for improved ADMET modeling	13
Enhanced Thompson sampling by roulette wheel selection for screening ultralarge combinatorial libraries	13
Prediction of blood–brain barrier and Caco-2 permeability through the Enalos Cloud Platform: combining contrastive learning and atom-attention message passing neural networks	12
Integrating QSAR modelling with reinforcement learning for Syk inhibitor discovery	12
kMoL: an open-source machine and federated learning library for drug discovery	12
graphpancake: a Python package for representing organic molecules as molecular graphs utilizing electronic structure theory	12
MDDI-SCL: predicting multi-type drug-drug interactions via supervised contrastive learning	12
Large language models open new way of AI-assisted molecule design for chemists	12
Naturally-meaningful and efficient descriptors: machine learning of material properties based on robust one-shot ab initio descriptors	12
FAME3R: an efficient, practical and reliable open-source tool for predicting phase 1 and phase 2 sites of metabolism	12
Building shape-focused pharmacophore models for effective docking screening	12
E-GuARD: expert-guided augmentation for the robust detection of compounds interfering with biological assays	12
Correction: Reconstruction of lossless molecular representations from fingerprints	12
DrugDiff: small molecule diffusion model with flexible guidance towards molecular properties	12
Physicochemical modelling of the retention mechanism of temperature-responsive polymeric columns for HPLC through machine learning algorithms	11
Benchmarking molecular conformer augmentation with context-enriched training: graph-based transformer versus GNN models	11
Machine learning-driven generation and screening of potential ionic liquids for cellulose dissolution	11
InflamNat: web-based database and predictor of anti-inflammatory natural products	11
A comparison of approaches to accessing existing biological and chemical relational databases via SPARQL	11
COMA: efficient structure-constrained molecular generation using contractive and margin losses	11
Small molecule autoencoders: architecture engineering to optimize latent space utility and sustainability	11
TraceMetrix: a traceable metabolomics interactive analysis platform	11
BitterMatch: recommendation systems for matching molecules with bitter taste receptors	11
Advantages of two quantum programming platforms in quantum computing and quantum chemistry	11
Generate what you can make: achieving in-house synthesizability with readily available resources in de novo drug design	11
Enhancing atom mapping with multitask learning and symmetry-aware deep graph matching	11
Relative molecule self-attention transformer	11
A molecule perturbation software library and its application to study the effects of molecular design constraints	11
TUCAN: A molecular identifier and descriptor applicable to the whole periodic table from hydrogen to oganesson	10
PermuteDDS: a permutable feature fusion network for drug-drug synergy prediction	10
Transfer learning across different chemical domains: virtual screening of organic materials with deep learning models pretrained on small molecule and chemical reaction data	10
Classification of battery compounds using structure-free Mendeleev encodings	10
Matched pairs demonstrate robustness against inter-assay variability	10
Contrastive explanations for machine learning predictions in chemistry	10
Reproducible MS/MS library cleaning pipeline in matchms	10
A comprehensive comparison of deep learning-based compound-target interaction prediction models to unveil guiding design principles	10
Syn-MolOpt: a synthesis planning-driven molecular optimization method using data-derived functional reaction templates	10
Double-head transformer neural network for molecular property prediction	10
Improving VAE based molecular representations for compound property prediction	10
Empowering federated learning for robust compound-protein interaction prediction across heterogeneous cross-pharma domains	10
PubChem synonym filtering process using crowdsourcing	10
StreaMD: the toolkit for high-throughput molecular dynamics simulations	10
Combatting over-specialization bias in growing chemical databases	9
BioisoIdentifier: an online free tool to investigate local structural replacements from PDB	9
DLM-DTI: a dual language model for the prediction of drug-target interaction with hint-based learning	9
TransExION: a transformer based explainable similarity metric for comparing IONS in tandem mass spectrometry	9
Improved estimation of intrinsic solubility of drug-like molecules through multi-task graph transformer	9
Exploring QSAR models for activity-cliff prediction	9
Principles and requirements for nanomaterial representations to facilitate machine processing and cooperation with nanoinformatics tools	9
Ai derivation and exploration of antibiotic class spaces	9
In-silico target prediction by ensemble chemogenomic model based on multi-scale information of chemical structures and protein sequences	9
Learnable protein representations in computational biology for predicting drug-target affinity	9
Barlow Twins deep neural network for advanced 1D drug–target interaction prediction	9
Enhancing molecular property prediction with auxiliary learning and task-specific adaptation	9
DeepRNA-DTI: a deep learning approach for RNA-compound interaction prediction with binding site interpretability	9
Paths to cheminformatics: Q&A with Rajarshi Guha	9
A pipeline for developing AI-driven models to predict molecular initiating events: a case study on neural tube defects	9
Application of the digital annealer unit in optimizing chemical reaction conditions for enhanced production yields	8
Mass-Suite: a novel open-source python package for high-resolution mass spectrometry data analysis	8
A novel approach for enhancing the potency of kinase inhibitors using topological water networks	8
Box embeddings for extending ontologies: a data-driven and interpretable approach	8
Uncertain of uncertainties? A comparison of uncertainty quantification metrics for chemical data sets	8
hERGAT: predicting hERG blockers using graph attention mechanism through atom- and molecule-level interaction analyses	8
An end-to-end method for predicting compound-protein interactions based on simplified homogeneous graph convolutional network and pre-trained language model	8
Large-scale evaluation of k-fold cross-validation ensembles for uncertainty estimation	8
PINNED: identifying characteristics of druggable human proteins using an interpretable neural network	8
Unveiling polyphenol-protein interactions: a comprehensive computational analysis	8
Positional embeddings and zero-shot learning using BERT for molecular-property prediction	8
Investigation of the structure-odor relationship using a Transformer model	8
Enhancing multi-task in vivo toxicity prediction via integrated knowledge transfer of chemical knowledge and in vitro toxicity information	8
Graph-based transformer to predict the octanol–water partition coefficient	8
xBitterT5: an explainable transformer-based framework with multimodal inputs for identifying bitter-taste peptides	8
From theory to experiment: transformer-based generation enables rapid discovery of novel reactions	8
Multi-fidelity graph neural networks for predicting toluene/water partition coefficients	8
SMPR: a structure-enhanced multimodal drug‒disease prediction model for drug repositioning and cold start	8
Context-dependent similarity analysis of analogue series for structure–activity relationship transfer based on a concept from natural language processing	7
CReM-pharm: de novo 3D pharmacophore-based design with synthetic accessibility awareness	7
Combining graph neural networks and transformers for few-shot nuclear receptor binding activity prediction	7
Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization	7
Integrating concept of pharmacophore with graph neural networks for chemical property prediction and interpretation	7
Multi-modal contrastive drug synergy prediction model guided by single modality	7
A new workflow for the effective curation of membrane permeability data from open ADME information	7
Data curation in cheminformatics: importance and implementation	7
Evaluating ligand docking methods for drugging protein–protein interfaces: insights from AlphaFold2 and molecular dynamics refinement	7
DeepSAT: Learning Molecular Structures from Nuclear Magnetic Resonance Data	7
CheMLT-F: multitask learning in biochemistry through transformer fusion	7
A look back at a pilot of the citation typing ontology	7