Journal of Cheminformatics

Papers
(The median citation count of Journal of Cheminformatics is 4. 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
Fifteen years of ChEMBL and its role in cheminformatics and drug discovery44
One chiral fingerprint to find them all44
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
Deep learning of multimodal networks with topological regularization for drug repositioning39
Advancements in thermochemical predictions: a multi-output thermodynamics-informed neural network approach39
Explaining compound activity predictions with a substructure-aware loss for graph neural networks38
Implementation of an open chemistry knowledge base with a Semantic Wiki38
Crossover operators for molecular graphs with an application to virtual drug screening37
The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC–TOF MS metabolome samples37
NanoBinder: a machine learning assisted nanobody binding prediction tool using Rosetta energy scores36
Shinyscreen: mass spectrometry data inspection and quality checking utility34
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
Bitter peptide prediction using graph neural networks32
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
Semi-automated workflow for molecular pair analysis and QSAR-assisted transformation space expansion30
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
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
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data25
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
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
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
VGSC-DB: an online database of voltage-gated sodium channels23
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
Implementation of a soft grading system for chemistry in a Moodle plugin22
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
Visualising lead optimisation series using reduced graphs21
Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations21
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
Chemical rules for optimization of chemical mutagenicity via matched molecular pairs analysis and machine learning methods20
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
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
DeepSA: a deep-learning driven predictor of compound synthesis accessibility18
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
Novel multi-objective affinity approach allows to identify pH-specific μ-opioid receptor agonists17
HepatoToxicity Portal (HTP): an integrated database of drug-induced hepatotoxicity knowledgebase and graph neural network-based prediction model16
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
Enhancing molecular property prediction with quantized GNN models15
TB-IECS: an accurate machine learning-based scoring function for virtual screening15
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
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
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
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
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
PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping12
Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors11
Pretraining graph transformers with atom-in-a-molecule quantum properties for improved ADMET modeling11
Machine learning approaches to optimize small-molecule inhibitors for RNA targeting11
Correction: Reconstruction of lossless molecular representations from fingerprints11
E-GuARD: expert-guided augmentation for the robust detection of compounds interfering with biological assays11
GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data11
Galaxy workflows for fragment-based virtual screening: a case study on the SARS-CoV-2 main protease11
Evaluating uncertainty-based active learning for accelerating the generalization of molecular property prediction11
MDDI-SCL: predicting multi-type drug-drug interactions via supervised contrastive learning11
Large language models open new way of AI-assisted molecule design for chemists11
A hybrid framework for improving uncertainty quantification in deep learning-based QSAR regression modeling11
PromptSMILES: prompting for scaffold decoration and fragment linking in chemical language models11
From papers to RDF-based integration of physicochemical data and adverse outcome pathways for nanomaterials11
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
Integrating QSAR modelling with reinforcement learning for Syk inhibitor discovery11
Naturally-meaningful and efficient descriptors: machine learning of material properties based on robust one-shot ab initio descriptors11
DrugDiff: small molecule diffusion model with flexible guidance towards molecular properties10
Building shape-focused pharmacophore models for effective docking screening10
Enhancing atom mapping with multitask learning and symmetry-aware deep graph matching10
kMoL: an open-source machine and federated learning library for drug discovery10
HobPre: accurate prediction of human oral bioavailability for small molecules10
COMA: efficient structure-constrained molecular generation using contractive and margin losses10
Machine learning-driven generation and screening of potential ionic liquids for cellulose dissolution10
Deep scaffold hopping with multimodal transformer neural networks10
Prediction of blood–brain barrier and Caco-2 permeability through the Enalos Cloud Platform: combining contrastive learning and atom-attention message passing neural networks10
Benchmarking molecular conformer augmentation with context-enriched training: graph-based transformer versus GNN models10
PUResNet: prediction of protein-ligand binding sites using deep residual neural network10
Advantages of two quantum programming platforms in quantum computing and quantum chemistry9
Correction to: TorsiFlex: an automatic generator of torsional conformers. Application to the twenty proteinogenic amino acids9
Processing binding data using an open-source workflow9
Double-head transformer neural network for molecular property prediction9
Small molecule autoencoders: architecture engineering to optimize latent space utility and sustainability9
PubChem synonym filtering process using crowdsourcing9
A molecule perturbation software library and its application to study the effects of molecular design constraints9
A comparison of approaches to accessing existing biological and chemical relational databases via SPARQL9
Physicochemical modelling of the retention mechanism of temperature-responsive polymeric columns for HPLC through machine learning algorithms9
Combatting over-specialization bias in growing chemical databases9
Improving VAE based molecular representations for compound property prediction9
Relative molecule self-attention transformer9
InflamNat: web-based database and predictor of anti-inflammatory natural products9
BitterMatch: recommendation systems for matching molecules with bitter taste receptors9
Generate what you can make: achieving in-house synthesizability with readily available resources in de novo drug design9
PermuteDDS: a permutable feature fusion network for drug-drug synergy prediction9
Classification of battery compounds using structure-free Mendeleev encodings8
Barlow Twins deep neural network for advanced 1D drug–target interaction prediction8
Explaining and avoiding failure modes in goal-directed generation of small molecules8
DLM-DTI: a dual language model for the prediction of drug-target interaction with hint-based learning8
A comprehensive comparison of deep learning-based compound-target interaction prediction models to unveil guiding design principles8
Syn-MolOpt: a synthesis planning-driven molecular optimization method using data-derived functional reaction templates8
GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations8
Reproducible MS/MS library cleaning pipeline in matchms8
Transfer learning across different chemical domains: virtual screening of organic materials with deep learning models pretrained on small molecule and chemical reaction data8
Matched pairs demonstrate robustness against inter-assay variability8
TUCAN: A molecular identifier and descriptor applicable to the whole periodic table from hydrogen to oganesson8
Improving the performance of models for one-step retrosynthesis through re-ranking8
StreaMD: the toolkit for high-throughput molecular dynamics simulations8
Exploring QSAR models for activity-cliff prediction7
Principles and requirements for nanomaterial representations to facilitate machine processing and cooperation with nanoinformatics tools7
From theory to experiment: transformer-based generation enables rapid discovery of novel reactions7
Integrating concept of pharmacophore with graph neural networks for chemical property prediction and interpretation7
An end-to-end method for predicting compound-protein interactions based on simplified homogeneous graph convolutional network and pre-trained language model7
Positional embeddings and zero-shot learning using BERT for molecular-property prediction7
TransExION: a transformer based explainable similarity metric for comparing IONS in tandem mass spectrometry7
FP-ADMET: a compendium of fingerprint-based ADMET prediction models7
MERMAID: an open source automated hit-to-lead method based on deep reinforcement learning7
QSPR modeling of selectivity at infinite dilution of ionic liquids7
UmetaFlow: an untargeted metabolomics workflow for high-throughput data processing and analysis7
Evaluating the generalizability of graph neural networks for predicting collision cross section7
Investigation of the structure-odor relationship using a Transformer model7
Large-scale evaluation of k-fold cross-validation ensembles for uncertainty estimation7
Mass-Suite: a novel open-source python package for high-resolution mass spectrometry data analysis7
BioisoIdentifier: an online free tool to investigate local structural replacements from PDB7
PINNED: identifying characteristics of druggable human proteins using an interpretable neural network7
An automated calculation pipeline for differential pair interaction energies with molecular force fields using the Tinker Molecular Modeling Package7
Unveiling polyphenol-protein interactions: a comprehensive computational analysis7
A workflow for deriving chemical entities from crystallographic data and its application to the Crystallography Open Database7
“DompeKeys”: a set of novel substructure-based descriptors for efficient chemical space mapping, development and structural interpretation of machine learning models, and indexing of large databases7
In-silico target prediction by ensemble chemogenomic model based on multi-scale information of chemical structures and protein sequences7
Enhancing molecular property prediction with auxiliary learning and task-specific adaptation7
Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization6
Uncertain of uncertainties? A comparison of uncertainty quantification metrics for chemical data sets6
Free and open-source QSAR-ready workflow for automated standardization of chemical structures in support of QSAR modeling6
Predicting RP-LC retention indices of structurally unknown chemicals from mass spectrometry data6
Computational Applications in Secondary Metabolite Discovery (CAiSMD): an online workshop6
Application of the digital annealer unit in optimizing chemical reaction conditions for enhanced production yields6
hERGAT: predicting hERG blockers using graph attention mechanism through atom- and molecule-level interaction analyses6
Accelerating the inference of string generation-based chemical reaction models for industrial applications6
Group graph: a molecular graph representation with enhanced performance, efficiency and interpretability6
MS2DeepScore: a novel deep learning similarity measure to compare tandem mass spectra6
Advancements in hand-drawn chemical structure recognition through an enhanced DECIMER architecture6
A look back at a pilot of the citation typing ontology6
Identifying uncertainty in physical–chemical property estimation with IFSQSAR6
Development of machine learning classifiers to predict compound activity on prostate cancer cell lines6
Improving the quality of chemical language model outcomes with atom-in-SMILES tokenization5
Biomedical data analyses facilitated by open cheminformatics workflows5
Generative design of compounds with desired potency from target protein sequences using a multimodal biochemical language model5
ABT-MPNN: an atom-bond transformer-based message-passing neural network for molecular property prediction5
Art driven by visual representations of chemical space5
A new workflow for the effective curation of membrane permeability data from open ADME information5
Molecular generation by Fast Assembly of (Deep)SMILES fragments5
Interpreting vibrational circular dichroism spectra: the Cai•factor for absolute configuration with confidence5
Efficient virtual high-content screening using a distance-aware transformer model5
Conditional reduction of the loss value versus reinforcement learning for biassing a de-novo drug design generator5
TorsiFlex: an automatic generator of torsional conformers. Application to the twenty proteinogenic amino acids5
DeepSAT: Learning Molecular Structures from Nuclear Magnetic Resonance Data5
Context-dependent similarity analysis of analogue series for structure–activity relationship transfer based on a concept from natural language processing5
Combining graph neural networks and transformers for few-shot nuclear receptor binding activity prediction5
InertDB as a generative AI-expanded resource of biologically inactive small molecules from PubChem5
Preventing lipophilic aggregation in cosolvent molecular dynamics simulations with hydrophobic probes using Plumed Automatic Restraining Tool (PART)5
Development of a chemogenomics library for phenotypic screening5
MEF-AlloSite: an accurate and robust Multimodel Ensemble Feature selection for the Allosteric Site identification model5
ELNdataBridge: facilitating data exchange and collaboration by linking Electronic Lab Notebooks via API4
Similarity-based pairing improves efficiency of siamese neural networks for regression tasks and uncertainty quantification4
AMADAR: a python-based package for large scale prediction of Diels–Alder transition state geometries and IRC path analysis4
Selecting lines for spectroscopic (re)measurements to improve the accuracy of absolute energies of rovibronic quantum states4
DeepDelta: predicting ADMET improvements of molecular derivatives with deep learning4
Two years of explicit CiTO annotations4
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