On the public citation graph

Development of a Novel Fingerprint for Chemical Reactions and Its Application to Large-Scale Reaction Classification and Similarity

0 signed · 219 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9783527618279.ch12openalex-snapshot
Reaction Classification and Knowledge Acquisition
inferredcites →https://doi.org/10.1002/9783527618279.ch43bopenalex-snapshot
Analysis of Reaction Information
inferredcites →https://doi.org/10.1002/cmdc.200700312openalex-snapshot
SyGMa: Combining Expert Knowledge and Empirical Scoring in the Prediction of Metabolites
inferredcites →https://doi.org/10.1002/minf.201400052openalex-snapshot
A Short Review of Chemical Reaction Database Systems, Computer‐Aided Synthesis Design, Reaction Prediction and Synthetic Feasibility
inferredcites →https://doi.org/10.1002/wcms.1140openalex-snapshot
Automatic reaction mapping and reaction center detection
inferredcites →https://doi.org/10.1016/s0022-2836(77)80200-3openalex-snapshot
The protein data bank: A computer-based archival file for macromolecular structures
inferredcites →https://doi.org/10.1016/s0040-4020(97)00911-3openalex-snapshot
Classification of organic reactions using similarity
inferredcites →https://doi.org/10.1016/s1574-1400(09)00513-1openalex-snapshot
Annual Reports in Computational Chemistry
inferredcites →https://doi.org/10.1021/ci00046a002openalex-snapshot
Atom pairs as molecular features in structure-activity studies: definition and applications
inferredcites →https://doi.org/10.1021/ci00054a008openalex-snapshot
Topological torsion: a new molecular descriptor for SAR applications. Comparison with other descriptors
inferredcites →https://doi.org/10.1021/ci00057a005openalex-snapshot
SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules
inferredcites →https://doi.org/10.1021/ci00068a008openalex-snapshot
CASREACT: more than a million reactions
inferredcites →https://doi.org/10.1021/ci00068a023openalex-snapshot
Building and refining a knowledge base for synthetic organic chemistry via the methodology of inductive and deductive machine learning
inferredcites →https://doi.org/10.1021/ci0503208openalex-snapshot
Molecular Transformations as a Way of Finding and Exploiting Consistent Local QSAR
inferredcites →https://doi.org/10.1021/ci100050topenalex-snapshot
Extended-Connectivity Fingerprints
inferredcites →https://doi.org/10.1021/ci300116popenalex-snapshot
Mining Electronic Laboratory Notebooks: Analysis, Retrosynthesis, and Reaction Based Enumeration
inferredcites →https://doi.org/10.1021/ci400442fopenalex-snapshot
Algorithm for Reaction Classification
inferredcites →https://doi.org/10.1021/ci800413mopenalex-snapshot
Knowledge-Based Approach to de Novo Design Using Reaction Vectors
inferredcites →https://doi.org/10.1021/ci9803381openalex-snapshot
Unsupervised Data Base Clustering Based on Daylight's Fingerprint and Tanimoto Similarity: A Fast and Automated Way To Cluster Small and Large Data Sets
inferredcites →https://doi.org/10.1021/jm200187yopenalex-snapshot
The Medicinal Chemist’s Toolbox: An Analysis of Reactions Used in the Pursuit of Drug Candidates
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1039/b602413kopenalex-snapshot
Analysis of the reactions used for the preparation of drug candidate molecules
inferredcites →https://doi.org/10.1093/nar/gkr777openalex-snapshot
ChEMBL: a large-scale bioactivity database for drug discovery
inferredcites →https://doi.org/10.1159/isbn.978-3-8055-9573-5openalex-snapshot
Theilheimer's Synthetic Methods of Organic Chemistry
inferredcites →https://doi.org/10.2307/1932409openalex-snapshot
Measures of the Amount of Ecologic Association Between Species
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/9781394249190.ch5openalex-snapshot
Virtual Screening and Lead Discovery
inferred← citeshttps://doi.org/10.1002/advs.202518063openalex-snapshot
CACLENS: A Multitask Deep Learning System for Enzyme Discovery
inferred← citeshttps://doi.org/10.1002/aic.18019openalex-snapshot
ConvPred : A deep learning‐based framework for predictions of potential organic reactions
inferred← citeshttps://doi.org/10.1002/aisy.201900143openalex-snapshot
Artificial Intelligence to Power the Future of Materials Science and Engineering
inferred← citeshttps://doi.org/10.1002/ange.201806920openalex-snapshot
Prediction of Major Regio‐, Site‐, and Diastereoisomers in Diels–Alder Reactions by Using Machine‐Learning: The Importance of Physically Meaningful Descriptors
inferred← citeshttps://doi.org/10.1002/anie.201806920openalex-snapshot
Prediction of Major Regio‐, Site‐, and Diastereoisomers in Diels–Alder Reactions by Using Machine‐Learning: The Importance of Physically Meaningful Descriptors
inferred← citeshttps://doi.org/10.1002/chem.201604556openalex-snapshot
Modelling Chemical Reasoning to Predict and Invent Reactions
inferred← citeshttps://doi.org/10.1002/chem.202401626openalex-snapshot
Computer‐Aided Synthesis Planning (CASP) and Machine Learning: Optimizing Chemical Reaction Conditions
inferred← citeshttps://doi.org/10.1002/cjce.25525openalex-snapshot
Artificial intelligence and machine learning at various stages and scales of process systems engineering
inferred← citeshttps://doi.org/10.1002/cjoc.202100273openalex-snapshot
Computational Analysis of Synthetic Planning: Past and Future
inferred← citeshttps://doi.org/10.1002/minf.202100119openalex-snapshot
Reaction Data Curation I: Chemical Structures and Transformations Standardization
inferred← citeshttps://doi.org/10.1002/minf.202100294openalex-snapshot
Prediction of the Chemical Context for Buchwald‐Hartwig Coupling Reactions
inferred← citeshttps://doi.org/10.1002/wcms.1604openalex-snapshot
Machine intelligence for chemical reaction space
inferred← citeshttps://doi.org/10.1007/978-3-031-37196-7_8openalex-snapshot
Synthesize in a Smart Way: A Brief Introduction to Intelligence and Automation in Organic Synthesis
inferred← citeshttps://doi.org/10.1007/978-981-95-6091-2_7openalex-snapshot
Graph Neural Networks (GNNs)
inferred← citeshttps://doi.org/10.1007/s10822-017-0044-3openalex-snapshot
Structure–reactivity modeling using mixture-based representation of chemical reactions
inferred← citeshttps://doi.org/10.1007/s11030-024-10889-7openalex-snapshot
Python tools for structural tasks in chemistry
inferred← citeshttps://doi.org/10.1007/s11030-026-11485-7openalex-snapshot
Enhancing ADMET property predictions using cross-aligned multimodal attention mechanisms
inferred← citeshttps://doi.org/10.1007/s12293-024-00414-6openalex-snapshot
Molecular representations in bio-cheminformatics
inferred← citeshttps://doi.org/10.1016/b978-0-12-409547-2.12345-5openalex-snapshot
Chemical Data Formats, Fingerprints, and Other Molecular Descriptions for Database Analysis and Searching
inferred← citeshttps://doi.org/10.1016/c2014-1-02188-6openalex-snapshot
Comprehensive Medicinal Chemistry III
inferred← citeshttps://doi.org/10.1016/j.actamat.2022.118255openalex-snapshot
Mechanical properties, failure mechanisms, and scaling laws of bicontinuous nanoporous metallic glasses
inferred← citeshttps://doi.org/10.1016/j.aichem.2025.100085openalex-snapshot
YieldFCP: Enhancing Reaction Yield Prediction via Fine-grained Cross-modal Pre-training
inferred← citeshttps://doi.org/10.1016/j.cscee.2024.100891openalex-snapshot
Statistical optimization and electrochemical analysis of gambir extract as a corrosion inhibitor for SS-316 in hydrochloric acid
inferred← citeshttps://doi.org/10.1016/j.drudis.2018.02.014openalex-snapshot
Computational prediction of chemical reactions: current status and outlook
inferred← citeshttps://doi.org/10.1016/j.drudis.2022.103356openalex-snapshot
Concepts and applications of chemical fingerprint for hit and lead screening
inferred← citeshttps://doi.org/10.1016/j.eng.2022.04.021openalex-snapshot
Artificial Intelligence for Retrosynthesis Prediction
inferred← citeshttps://doi.org/10.1016/j.gce.2024.06.003openalex-snapshot
Developing deep learning-based large-scale organic reaction classification model via sigma-profiles
inferred← citeshttps://doi.org/10.1016/j.ica.2026.123394openalex-snapshot
Mathematical concepts for representation of ligand permutation, stereochemistry, and bonding and integration with AI/ML: Application to ATP synthesis/hydrolysis
inferred← citeshttps://doi.org/10.1016/j.ijoes.2024.100887openalex-snapshot
Artificial intelligence-aided electrochemical sensors for capturing and analyzing fingerprint profiles of medicinal materials
inferred← citeshttps://doi.org/10.1016/j.mencom.2021.11.003openalex-snapshot
Machine learning modelling of chemical reaction characteristics: yesterday, today, tomorrow
inferred← citeshttps://doi.org/10.1016/j.namjnl.2025.100012openalex-snapshot
AI-driven parametrization of Michaelis–Menten maximal velocity: Advancing in silico new approach methodologies (NAMs)
inferred← citeshttps://doi.org/10.1021/acs.chemmater.2c03010openalex-snapshot
Interpretable Machine Learning Enabled Inorganic Reaction Classification and Synthesis Condition Prediction
inferred← citeshttps://doi.org/10.1021/acs.energyfuels.3c05019openalex-snapshot
Creating a Reaction Data Set Labeled with Reaction Class for Automated Reaction Classification for ReaxFF Molecular Dynamics Simulations of Realistic Fuel Pyrolysis
inferred← citeshttps://doi.org/10.1021/acs.jchemed.5c00959openalex-snapshot
Teaching Computer-Assisted Retrosynthesis Reaction Prediction with Open-Source Software
inferred← citeshttps://doi.org/10.1021/acs.jcim.0c00403openalex-snapshot
Data Augmentation and Pretraining for Template-Based Retrosynthetic Prediction in Computer-Aided Synthesis Planning
inferred← citeshttps://doi.org/10.1021/acs.jcim.0c01097openalex-snapshot
Permutationally Invariant Deep Learning Approach to Molecular Fingerprinting with Application to Compound Mixtures
inferred← citeshttps://doi.org/10.1021/acs.jcim.1c00297openalex-snapshot
Learning Chemistry of Complex Reaction Systems via a Python First-Principles Reaction Rule Stencil (pReSt) Generator
inferred← citeshttps://doi.org/10.1021/acs.jcim.1c01140openalex-snapshot
Call for a Public Open Database of All Chemical Reactions
inferred← citeshttps://doi.org/10.1021/acs.jcim.1c01192openalex-snapshot
Influence of Template Size, Canonicalization, and Exclusivity for Retrosynthesis and Reaction Prediction Applications
inferred← citeshttps://doi.org/10.1021/acs.jcim.1c01467openalex-snapshot
Unified Deep Learning Model for Multitask Reaction Predictions with Explanation
inferred← citeshttps://doi.org/10.1021/acs.jcim.3c00892openalex-snapshot
Structure-Based Reaction Descriptors for Predicting Rate Constants by Machine Learning: Application to Hydrogen Abstraction from Alkanes by CH 3 /H/O Radicals
inferred← citeshttps://doi.org/10.1021/acs.jcim.3c01685openalex-snapshot
Do Chemformers Dream of Organic Matter? Evaluating a Transformer Model for Multistep Retrosynthesis
inferred← citeshttps://doi.org/10.1021/acs.jcim.4c00004openalex-snapshot
Exploring Chemical Reaction Space with Machine Learning Models: Representation and Feature Perspective
inferred← citeshttps://doi.org/10.1021/acs.jcim.4c00157openalex-snapshot
Self-Supervised Contrastive Molecular Representation Learning with a Chemical Synthesis Knowledge Graph
inferred← citeshttps://doi.org/10.1021/acs.jcim.4c01787openalex-snapshot
HiRXN: Hierarchical Attention-Based Representation Learning for Chemical Reaction
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00722openalex-snapshot
Classifying Force Spectroscopy of DNA Pulling Measurements Using Supervised and Unsupervised Machine Learning Methods
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c01404openalex-snapshot
Improving Reaction Yield Prediction with Chemical Atom-Level Reaction Learning
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c01797openalex-snapshot
Precedent Finder: Locating Pareto-Optimal Reactions
inferred← citeshttps://doi.org/10.1021/acs.jcim.5c02645openalex-snapshot
ChemTorch: A Deep Learning Framework for Benchmarking and Developing Chemical Reaction Property Prediction Models
inferred← citeshttps://doi.org/10.1021/acs.jcim.6b00564openalex-snapshot
What’s What: The (Nearly) Definitive Guide to Reaction Role Assignment
inferred← citeshttps://doi.org/10.1021/acs.jcim.6c01458openalex-snapshot
Pathway-Aware Template-Based Retrosynthesis
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00622openalex-snapshot
SCScore: Synthetic Complexity Learned from a Reaction Corpus
inferred← citeshttps://doi.org/10.1021/acs.jcim.7b00656openalex-snapshot
Multiclassification Prediction of Enzymatic Reactions for Oxidoreductases and Hydrolases Using Reaction Fingerprints and Machine Learning Methods
inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00286openalex-snapshot
Perturbation-Theory and Machine Learning (PTML) Model for High-Throughput Screening of Parham Reactions: Experimental and Theoretical Studies
inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00801openalex-snapshot
Enhancing Retrosynthetic Reaction Prediction with Deep Learning Using Multiscale Reaction Classification
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00537openalex-snapshot
Development and Application of a Data-Driven Reaction Classification Model: Comparison of an Electronic Lab Notebook and Medicinal Chemistry Literature
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00721openalex-snapshot
What Does the Machine Learn? Knowledge Representations of Chemical Reactivity
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00929openalex-snapshot
Predicting the Feasibility of Copper(I)-Catalyzed Alkyne–Azide Cycloaddition Reactions Using a Recurrent Neural Network with a Self-Attention Mechanism
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b00949openalex-snapshot
Predicting Retrosynthetic Reactions Using Self-Corrected Transformer Neural Networks
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b01141openalex-snapshot
Context Aware Data-Driven Retrosynthetic Analysis
inferred← citeshttps://doi.org/10.1021/acs.jctc.6c00815openalex-snapshot
Relation-Aware Pretraining and Reaction Center Modeling for Chemical Reaction Graph Representation Learning
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6b00153openalex-snapshot
Big Data from Pharmaceutical Patents: A Computational Analysis of Medicinal Chemists’ Bread and Butter
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.9b02120openalex-snapshot
Current and Future Roles of Artificial Intelligence in Medicinal Chemistry Synthesis
inferred← citeshttps://doi.org/10.1021/acs.jpca.3c04779openalex-snapshot
Recent Applications of Machine Learning in Molecular Property and Chemical Reaction Outcome Predictions
inferred← citeshttps://doi.org/10.1021/acs.jpca.4c01592openalex-snapshot
Identification of Reaction Network Hypotheses for Complex Feedstocks from Spectroscopic Measurements with Minimal Human Intervention
inferred← citeshttps://doi.org/10.1021/acs.organomet.2c00051openalex-snapshot
Data-Driven Analysis of Reactions Catalyzed by [CoCp*(CO)I2]
inferred← citeshttps://doi.org/10.1021/acscentsci.6b00219openalex-snapshot
Neural Networks for the Prediction of Organic Chemistry Reactions
inferred← citeshttps://doi.org/10.1021/acscentsci.8b00357openalex-snapshot
Using Machine Learning To Predict Suitable Conditions for Organic Reactions
inferred← citeshttps://doi.org/10.1021/acscentsci.9b00297openalex-snapshot
A Mixed Quantum Chemistry/Machine Learning Approach for the Fast and Accurate Prediction of Biochemical Redox Potentials and Its Large-Scale Application to 315 000 Redox Reactions
inferred← citeshttps://doi.org/10.1021/acscentsci.9b00576openalex-snapshot
Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction
inferred← citeshttps://doi.org/10.1021/acsomega.5c03722openalex-snapshot
Role of Structural, Pharmacokinetic, and Energy Properties in the High-Throughput Prediction of Redox Potentials for Organic Molecules with Experimental Calibration
inferred← citeshttps://doi.org/10.1021/jacs.2c05302openalex-snapshot
Machine Learning Yield Prediction from NiCOlit, a Small-Size Literature Data Set of Nickel Catalyzed C–O Couplings
inferred← citeshttps://doi.org/10.1021/jacsau.3c00607openalex-snapshot
SynCluster: Reaction Type Clustering and Recommendation Framework for Synthesis Planning
inferred← citeshttps://doi.org/10.1021/jacsau.5c00289openalex-snapshot
HiCLR: Knowledge-Induced Hierarchical Contrastive Learning with Retrosynthesis Prediction Yields a Reaction Foundation Model
inferred← citeshttps://doi.org/10.1038/nature25978openalex-snapshot
Planning chemical syntheses with deep neural networks and symbolic AI
inferred← citeshttps://doi.org/10.1038/s41467-019-09440-2openalex-snapshot
Automatic mapping of atoms across both simple and complex chemical reactions
inferred← citeshttps://doi.org/10.1038/s41467-021-21895-wopenalex-snapshot
Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias
inferred← citeshttps://doi.org/10.1038/s41467-021-22951-1openalex-snapshot
Inferring experimental procedures from text-based representations of chemical reactions
inferred← citeshttps://doi.org/10.1038/s41467-024-52048-4openalex-snapshot
Site-specific template generative approach for retrosynthetic planning
inferred← citeshttps://doi.org/10.1038/s41467-024-54611-5openalex-snapshot
Systematic, computational discovery of multicomponent and one-pot reactions
inferred← citeshttps://doi.org/10.1038/s41524-024-01290-xopenalex-snapshot
Growing strings in a chemical reaction space for searching retrosynthesis pathways
inferred← citeshttps://doi.org/10.1038/s41557-018-0021-zopenalex-snapshot
Organic synthesis provides opportunities to transform drug discovery
inferred← citeshttps://doi.org/10.1038/s41570-021-00260-xopenalex-snapshot
Organic reactivity from mechanism to machine learning
inferred← citeshttps://doi.org/10.1038/s41597-026-07260-wopenalex-snapshot
SynRXN: An Open Benchmark and Curated Dataset for Computational Reaction Modeling
inferred← citeshttps://doi.org/10.1038/s41598-017-02303-0openalex-snapshot
Predicting the outcomes of organic reactions via machine learning: are current descriptors sufficient?
inferred← citeshttps://doi.org/10.1038/s42004-024-01101-wopenalex-snapshot
Exploring the combinatorial explosion of amine–acid reaction space via graph editing
inferred← citeshttps://doi.org/10.1038/s42256-020-00284-wopenalex-snapshot
Mapping the space of chemical reactions using attention-based neural networks
inferred← citeshttps://doi.org/10.1038/s42256-021-00367-2openalex-snapshot
Reusability report: Learning the language of synthetic methods used in medicinal chemistry
inferred← citeshttps://doi.org/10.1038/s42256-023-00764-9openalex-snapshot
Bridging the gap between chemical reaction pretraining and conditional molecule generation with a unified model
inferred← citeshttps://doi.org/10.1038/s42256-025-01032-8openalex-snapshot
Bridging chemistry and artificial intelligence by a reaction description language
inferred← citeshttps://doi.org/10.1038/s42256-025-01098-4openalex-snapshot
A unified pre-trained deep learning framework for cross-task reaction performance prediction and synthesis planning
inferred← citeshttps://doi.org/10.1039/9781839160233-00169openalex-snapshot
Machine Learning for Chemical Synthesis
inferred← citeshttps://doi.org/10.1039/c7ce00738hopenalex-snapshot
A publicly available crystallisation data set and its application in machine learning
inferred← citeshttps://doi.org/10.1039/c8sc02339eopenalex-snapshot
“Found in Translation”: predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models
inferred← citeshttps://doi.org/10.1039/c9re00019dopenalex-snapshot
Making better decisions during synthetic route design: leveraging prediction to achieve greenness-by-design
inferred← citeshttps://doi.org/10.1039/c9sc03666kopenalex-snapshot
Automatic retrosynthetic route planning using template-free models
inferred← citeshttps://doi.org/10.1039/d0sc04896hopenalex-snapshot
Machine learning meets mechanistic modelling for accurate prediction of experimental activation energies
inferred← citeshttps://doi.org/10.1039/d0sc05078dopenalex-snapshot
Evaluating and clustering retrosynthesis pathways with learned strategy
inferred← citeshttps://doi.org/10.1039/d0sc05251eopenalex-snapshot
BonDNet: a graph neural network for the prediction of bond dissociation energies for charged molecules
inferred← citeshttps://doi.org/10.1039/d1cp04422bopenalex-snapshot
Progress towards machine learning reaction rate constants
inferred← citeshttps://doi.org/10.1039/d1cp05878aopenalex-snapshot
Reproducing the invention of a named reaction: zero-shot prediction of unseen chemical reactions
inferred← citeshttps://doi.org/10.1039/d1dd00006copenalex-snapshot
Reaction classification and yield prediction using the differential reaction fingerprint DRFP
inferred← citeshttps://doi.org/10.1039/d1sc06515gopenalex-snapshot
Improving machine learning performance on small chemical reaction data with unsupervised contrastive pretraining
inferred← citeshttps://doi.org/10.1039/d2dd00083kopenalex-snapshot
Data-driven generation of perturbation networks for relative binding free energy calculations
inferred← citeshttps://doi.org/10.1039/d2re00309kopenalex-snapshot
AI-driven hypergraph network of organic chemistry: network statistics and applications in reaction classification
inferred← citeshttps://doi.org/10.1039/d2sc01334gopenalex-snapshot
Low-cost prediction of molecular and transition state partition functions via machine learning
inferred← citeshttps://doi.org/10.1039/d2sc03016kopenalex-snapshot
Automated stopped-flow library synthesis for rapid optimisation and machine learning directed experimentation
inferred← citeshttps://doi.org/10.1039/d2sc05089gopenalex-snapshot
Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
inferred← citeshttps://doi.org/10.1039/d2sc06798fopenalex-snapshot
Reagent prediction with a molecular transformer improves reaction data quality
inferred← citeshttps://doi.org/10.1039/d3cp05935aopenalex-snapshot
Generating a skeleton reaction network for reactions of large-scale ReaxFF MD pyrolysis simulations based on a machine learning predicted reaction class
inferred← citeshttps://doi.org/10.1039/d3dd00096fopenalex-snapshot
Bayesian optimisation for additive screening and yield improvements – beyond one-hot encoding
inferred← citeshttps://doi.org/10.1039/d3dd00175jopenalex-snapshot
Benchmarking machine-readable vectors of chemical reactions on computed activation barriers
inferred← citeshttps://doi.org/10.1039/d4dd00007bopenalex-snapshot
Investigating the reliability and interpretability of machine learning frameworks for chemical retrosynthesis
inferred← citeshttps://doi.org/10.1039/d4sc07320gopenalex-snapshot
Digitization of molecular complexity with machine learning
inferred← citeshttps://doi.org/10.1039/d5dd00367aopenalex-snapshot
SynCat: molecule-level attention graph neural network for precise reaction classification
inferred← citeshttps://doi.org/10.1039/d5sc04957aopenalex-snapshot
Data-driven recommendation of agents, temperature, and equivalence ratios for organic synthesis
inferred← citeshttps://doi.org/10.1063/5.0096027openalex-snapshot
Successes and challenges in using machine-learned activation energies in kinetic simulations
inferred← citeshttps://doi.org/10.1070/rcr4746openalex-snapshot
Artificial intelligence in synthetic chemistry: achievements and prospects
inferred← citeshttps://doi.org/10.1073/pnas.2520070123openalex-snapshot
Dual-encoder contrastive learning accelerates enzyme discovery
inferred← citeshttps://doi.org/10.1088/2632-2153/aba822openalex-snapshot
Thousands of reactants and transition states for competing E2 and S N 2 reactions
inferred← citeshttps://doi.org/10.1088/2632-2153/acee42openalex-snapshot
Comment on ‘Physics-based representations for machine learning properties of chemical reactions’
inferred← citeshttps://doi.org/10.1088/2632-2153/ad5413openalex-snapshot
Completion of partial chemical equations
inferred← citeshttps://doi.org/10.1088/2632-2153/ad9709openalex-snapshot
Transferability of atom-based neural networks
inferred← citeshttps://doi.org/10.1088/2632-2153/adfd37openalex-snapshot
Accelerating reaction rate predictions: a machine learning approach using a novel quantum chemical property for nucleophilic aromatic substitutions
inferred← citeshttps://doi.org/10.1093/bioinformatics/btae558openalex-snapshot
Chemical reaction enhanced graph learning for molecule representation
inferred← citeshttps://doi.org/10.1093/bioinformatics/btaf355openalex-snapshot
CSGL: chemical synthesis graph learning for molecule representation
inferred← citeshttps://doi.org/10.1093/bioinformatics/btag142openalex-snapshot
Enzyme association for environmental biotransformation reactions through contrastive learning of reaction center-specific fingerprints
inferred← citeshttps://doi.org/10.1093/bioinformatics/btag193openalex-snapshot
A cross-attentive multi-task graph learning framework for chemical reaction modeling
inferred← citeshttps://doi.org/10.1093/bioinformatics/btv416openalex-snapshot
RxnSim: a tool to compare biochemical reactions
inferred← citeshttps://doi.org/10.1093/nar/gkae405openalex-snapshot
REME: an integrated platform for reaction enzyme mining and evaluation
inferred← citeshttps://doi.org/10.1093/nar/gkv1253openalex-snapshot
SureChEMBL: a large-scale, chemically annotated patent document database
inferred← citeshttps://doi.org/10.1101/2025.10.13.682169openalex-snapshot
Structured Chemical Reaction Modeling with Multitask Graph Neural Networks
inferred← citeshttps://doi.org/10.1109/ascc70886.2026.11702276openalex-snapshot
Hierarchical Contrastive Learning for Organic Reaction Similarity Evaluation with its Application in Retrosynthesis
inferred← citeshttps://doi.org/10.1109/bibm55620.2022.9995338openalex-snapshot
Graph-based Reaction Classification by Contrasting between Precursors and Products
inferred← citeshttps://doi.org/10.1109/bigdata59044.2023.10386300openalex-snapshot
Mining Large-Scale Knowledge Graphs for Chemical Reaction Fingerprints
inferred← citeshttps://doi.org/10.1126/sciadv.abe4166openalex-snapshot
Extraction of organic chemistry grammar from unsupervised learning of chemical reactions
inferred← citeshttps://doi.org/10.1142/9789813235533_0006openalex-snapshot
Chemical reaction vector embeddings: towards predicting drug metabolism in the human gut microbiome
inferred← citeshttps://doi.org/10.1145/3109859.3109895openalex-snapshot
Chemical Reactant Recommendation Using a Network of Organic Chemistry
inferred← citeshttps://doi.org/10.1145/3746252.3761323openalex-snapshot
Proto-Yield: An Uncertainty-Aware Prototype Network for Yield Prediction in Real-world Chemical Reactions
inferred← citeshttps://doi.org/10.1186/s12859-018-2248-5openalex-snapshot
SimCAL: a flexible tool to compute biochemical reaction similarity
inferred← citeshttps://doi.org/10.1186/s13321-020-00452-5openalex-snapshot
CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumeration
inferred← citeshttps://doi.org/10.1186/s13321-020-00460-5openalex-snapshot
Molecular representations in AI-driven drug discovery: a review and practical guide
inferred← citeshttps://doi.org/10.1186/s13321-021-00579-zopenalex-snapshot
Uncertainty-aware prediction of chemical reaction yields with graph neural networks
inferred← citeshttps://doi.org/10.1186/s13321-022-00594-8openalex-snapshot
Improving the performance of models for one-step retrosynthesis through re-ranking
inferred← citeshttps://doi.org/10.1186/s13321-023-00715-xopenalex-snapshot
MetaRF: attention-based random forest for reaction yield prediction with a few trails
inferred← citeshttps://doi.org/10.1186/s13321-024-00805-4openalex-snapshot
Enhancing chemical synthesis: a two-stage deep neural network for predicting feasible reaction conditions
inferred← citeshttps://doi.org/10.1186/s13321-024-00815-2openalex-snapshot
Prediction of chemical reaction yields with large-scale multi-view pre-training
inferred← citeshttps://doi.org/10.1186/s13321-024-00834-zopenalex-snapshot
Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices
inferred← citeshttps://doi.org/10.1186/s13321-024-00875-4openalex-snapshot
Reaction rebalancing: a novel approach to curating reaction databases
inferred← citeshttps://doi.org/10.1186/s13321-025-00987-5openalex-snapshot
Enhancing chemical reaction search through contrastive representation learning and human-in-the-loop
inferred← citeshttps://doi.org/10.1186/s13321-025-01118-wopenalex-snapshot
NOCTIS: open-source toolkit that turns reaction data into actionable graph networks
inferred← citeshttps://doi.org/10.1186/s13321-025-01130-0openalex-snapshot
The consolidation of open-source computer-assisted chemical synthesis data into a comprehensive database
inferred← citeshttps://doi.org/10.1360/ssc-2025-0111openalex-snapshot
The converging moment of chemistry and artificial intelligence: a review and outlook
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1006471openalex-snapshot
Quantum chemistry reveals thermodynamic principles of redox biochemistry
inferred← citeshttps://doi.org/10.1515/revce-2024-0027openalex-snapshot
Machine learning applications for thermochemical and kinetic property prediction
inferred← citeshttps://doi.org/10.17122/ogbus-2019-4-243-268openalex-snapshot
USING METHOD OF MACHINE TRAINING AND ARTIFICIAL INTELLIGENCE IN CHEMICAL TECHNOLOGY. PART I
inferred← citeshttps://doi.org/10.17586/2226-1494-2020-20-6-863-870openalex-snapshot
Prediction of reaction conditions by deep learning techniques
inferred← citeshttps://doi.org/10.21203/rs.3.rs-10847205/v1openalex-snapshot
Reaction-Center-Guided Reranking of Transformer Product Predictions with a Product-Conditioned Graph Neural Network
inferred← citeshttps://doi.org/10.21203/rs.3.rs-4276245/v1openalex-snapshot
Artificial intelligence-based parametrization of Michaelis–Menten maximal velocity: Toward in silico New Approach Methodologies (NAMs)
inferred← citeshttps://doi.org/10.21203/rs.3.rs-8855497/v1openalex-snapshot
Fragment Tree Reconciliation (FTR) for Space Applications
inferred← citeshttps://doi.org/10.21741/9781644902530-4openalex-snapshot
Artificial Intelligence in Material Genomics
inferred← citeshttps://doi.org/10.26434/chemrxiv-2021-x5sj7openalex-snapshot
National Institutes of Health (NIH) Workshop on Reaction Informatics
inferred← citeshttps://doi.org/10.26434/chemrxiv-2022-4kzp1openalex-snapshot
Data-driven Reaction Template Fingerprints
inferred← citeshttps://doi.org/10.26434/chemrxiv-2022-nll2jopenalex-snapshot
Bayesian optimisation for additive screening and yieldimprovements in chemical reactions – beyond one-hot encodings
inferred← citeshttps://doi.org/10.26434/chemrxiv-2022-nll2j-v2openalex-snapshot
Bayesian optimisation for additive screening and yieldimprovements in chemical reactions – beyond one-hot encoding
inferred← citeshttps://doi.org/10.26434/chemrxiv-2023-6rbfjopenalex-snapshot
Recommending Multiple Reaction Conditions UsingTwo-Stage Deep Neural Networks
inferred← citeshttps://doi.org/10.26434/chemrxiv-2023-89v4qopenalex-snapshot
Transform Descriptors for template free reaction classification
inferred← citeshttps://doi.org/10.26434/chemrxiv.11659563.v1openalex-snapshot
Integrating Deep Neural Networks and Symbolic Inference for Organic Reactivity Prediction
inferred← citeshttps://doi.org/10.26434/chemrxiv.11869692.v4openalex-snapshot
RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist
inferred← citeshttps://doi.org/10.26434/chemrxiv.13273310openalex-snapshot
Completion of Partial Reaction Equations
inferred← citeshttps://doi.org/10.26434/chemrxiv.13273310.v1openalex-snapshot
Completion of Partial Reaction Equations
inferred← citeshttps://doi.org/10.26434/chemrxiv.13280495openalex-snapshot
A Quick Policy to Filter Reactions Based on Feasibility in AI-Guided Retrosynthetic Planning
inferred← citeshttps://doi.org/10.26434/chemrxiv.13280495.v1openalex-snapshot
A Quick Policy to Filter Reactions Based on Feasibility in AI-Guided Retrosynthetic Planning
inferred← citeshttps://doi.org/10.26434/chemrxiv.8168354.v1openalex-snapshot
Automatic Retrosynthetic Pathway Planning Using Template-free Models
inferred← citeshttps://doi.org/10.26434/chemrxiv.8427776openalex-snapshot
Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural Networks
inferred← citeshttps://doi.org/10.26434/chemrxiv.9897365.v1openalex-snapshot
Data-Driven Chemical Reaction Classification with Attention-Based Neural Networks
inferred← citeshttps://doi.org/10.26434/chemrxiv.9897365.v2openalex-snapshot
Data-Driven Chemical Reaction Classification, Fingerprinting and Clustering using Attention-Based Neural Networks
inferred← citeshttps://doi.org/10.33774/chemrxiv-2021-mc870openalex-snapshot
Reaction Classification and Yield Prediction using the Differential Reaction Fingerprint DRFP
inferred← citeshttps://doi.org/10.3389/fceng.2020.00005openalex-snapshot
Artificial Intelligence for Computer-Aided Synthesis In Flow: Analysis and Selection of Reaction Components
inferred← citeshttps://doi.org/10.3389/fchem.2018.00199openalex-snapshot
Computational Chemical Synthesis Analysis and Pathway Design
inferred← citeshttps://doi.org/10.3390/app13095311openalex-snapshot
Learning Hierarchical Representations for Explainable Chemical Reaction Prediction
inferred← citeshttps://doi.org/10.3390/biom10111486openalex-snapshot
Virtual Screening for Reactive Natural Products and Their Probable Artifacts of Solvolysis and Oxidation
inferred← citeshttps://doi.org/10.48550/arxiv.2012.11522openalex-snapshot
Barking up the right tree: an approach to search over molecule synthesis DAGs
inferred← citeshttps://doi.org/10.48550/arxiv.2104.03279openalex-snapshot
Modern Hopfield Networks for Few- and Zero-Shot Reaction Template Prediction
inferred← citeshttps://doi.org/10.59717/j.xinn-inform.2026.100026openalex-snapshot
A comprehensive survey of AI-based retrosynthesis planning: Datasets, models, and tools
inferred← citeshttps://doi.org/10.6084/m9.figshare.19367575openalex-snapshot
Additional file 1 of Improving the performance of models for one-step retrosynthesis through re-ranking
inferred← citeshttps://doi.org/10.6084/m9.figshare.25059473openalex-snapshot
Additional file 1 of Enhancing chemical synthesis: a two-stage deep neural network for predicting feasible reaction conditions
inferred← citeshttps://doi.org/10.6084/m9.figshare.26685387openalex-snapshot
Additional file 1 of Prediction of chemical reaction yields with large-scale multi-view pre-training
inferred← citeshttps://doi.org/10.6084/m9.figshare.26699678openalex-snapshot
Additional file 1 of Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices
inferred← citeshttps://doi.org/10.6084/m9.figshare.26699681openalex-snapshot
Additional file 2 of Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices
inferred← citeshttps://doi.org/10.70675/ab76b9fcze4cbz45a3z950dz023b6506d0acopenalex-snapshot
Predictive models for kinetic and thermodynamic parameters of reactions
inferred← citeshttps://doi.org/10.7554/elife.82401openalex-snapshot
SIMMER employs similarity algorithms to accurately identify human gut microbiome species and enzymes capable of known chemical transformations
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.