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Machine Learning Methods for Property Prediction in Chemoinformatics:Quo Vadis?
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Linear Programming Boosting via Column Generation
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Statistical Asymptotic Theory of Active Learning
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Machine Learning in Drug Design
inferred← citeshttps://doi.org/10.1039/c5tx00406copenalex-snapshot
Improving the prediction of organism-level toxicity through integration of chemical, protein target and cytotoxicity qHTS data
inferred← citeshttps://doi.org/10.1039/c7sc02664aopenalex-snapshot
MoleculeNet: a benchmark for molecular machine learning
inferred← citeshttps://doi.org/10.1039/d2dd00136eopenalex-snapshot
Generating structural alerts from toxicology datasets using the local interpretable model-agnostic explanations method
inferred← citeshttps://doi.org/10.1039/d2dd00146bopenalex-snapshot
Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS
inferred← citeshttps://doi.org/10.1039/d3ma00535fopenalex-snapshot
Machine learning-based q-RASPR predictions of detonation heat for nitrogen-containing compounds
inferred← citeshttps://doi.org/10.1039/d4ya00215fopenalex-snapshot
Predicting the performance and stability parameters of energetic materials (EMs) using a machine learning-based q-RASPR approach
inferred← citeshttps://doi.org/10.1063/1.5054968openalex-snapshot
Machine learning model for non-equilibrium structures and energies of simple molecules
inferred← citeshttps://doi.org/10.1063/5.0123091openalex-snapshot
Artificial intelligence: Evolving role in drug design
inferred← citeshttps://doi.org/10.1080/08927022.2018.1450982openalex-snapshot
Representing molecular and materials data for unsupervised machine learning
inferred← citeshttps://doi.org/10.1080/15376516.2024.2387733openalex-snapshot
Using machine learning to classify the immunosuppressive activity of per- and polyfluoroalkyl substances
inferred← citeshttps://doi.org/10.1080/17425255.2023.2298827openalex-snapshot
Where developmental toxicity meets explainable artificial intelligence: state-of-the-art and perspectives
inferred← citeshttps://doi.org/10.1080/17435390.2023.2186280openalex-snapshot
Efficient predictions of cytotoxicity of TiO2-based multi-component nanoparticles using a machine learning-based q-RASAR approach
inferred← citeshttps://doi.org/10.1080/17460441.2016.1201262openalex-snapshot
A renaissance of neural networks in drug discovery
inferred← citeshttps://doi.org/10.1080/17460441.2019.1593368openalex-snapshot
Is one-shot learning a viable option in drug discovery?
inferred← citeshttps://doi.org/10.1080/17460441.2020.1745183openalex-snapshot
The power of deep learning to ligand-based novel drug discovery
inferred← citeshttps://doi.org/10.1080/17460441.2021.1887133openalex-snapshot
Practical constraints with machine learning in drug discovery
inferred← citeshttps://doi.org/10.1088/1361-6528/aa82e5openalex-snapshot
Machine learning and genetic algorithm prediction of energy differences between electronic calculations of graphene nanoflakes
inferred← citeshttps://doi.org/10.1093/bib/bbv037openalex-snapshot
Building a virtual ligand screening pipeline using free software: a survey
inferred← citeshttps://doi.org/10.1093/bioinformatics/btac112openalex-snapshot
Advanced graph and sequence neural networks for molecular property prediction and drug discovery
inferred← citeshttps://doi.org/10.1103/physreva.104.032416openalex-snapshot
Quantum evolution kernel: Machine learning on graphs with programmable arrays of qubits
inferred← citeshttps://doi.org/10.1109/bibm47256.2019.8982989openalex-snapshot
Interpretable Prediction of Protein-Ligand Interaction by Convolutional Neural Network
inferred← citeshttps://doi.org/10.1109/bibm52615.2021.9669478openalex-snapshot
CurrMG: A Curriculum Learning Approach for Graph Based Molecular Property Prediction
inferred← citeshttps://doi.org/10.1109/sai.2016.7555985openalex-snapshot
Recent advances for handling imbalancement and uncertainty in labelling in medicinal chemistry data analysis
inferred← citeshttps://doi.org/10.1111/cbdd.12294openalex-snapshot
Modeling of Compound Profiling Experiments Using Support Vector Machines
inferred← citeshttps://doi.org/10.1111/cbdd.14057openalex-snapshot
Machine learning approaches and their applications in drug discovery and design
inferred← citeshttps://doi.org/10.1145/3511808.3557085openalex-snapshot
Graph Neural Networks Pretraining Through Inherent Supervision for Molecular Property Prediction
inferred← citeshttps://doi.org/10.1146/annurev-biodatasci-122120-124216openalex-snapshot
Machine Learning in Chemoinformatics and Medicinal Chemistry
inferred← citeshttps://doi.org/10.1155/2013/863592openalex-snapshot
Development of Conformation Independent Computational Models for the Early Recognition of Breast Cancer Resistance Protein Substrates
inferred← citeshttps://doi.org/10.1177/11779322221090349openalex-snapshot
Applied Machine Learning Toward Drug Discovery Enhancement: Leishmaniases as a Case Study
inferred← citeshttps://doi.org/10.1177/24725552211017520openalex-snapshot
Validating ADME QSAR Models Using Marketed Drugs
inferred← citeshttps://doi.org/10.1186/1758-2946-6-21openalex-snapshot
Self organising hypothesis networks: a new approach for representing and structuring SAR knowledge
inferred← citeshttps://doi.org/10.1186/s12859-020-03645-9openalex-snapshot
Convolutional architectures for virtual screening
inferred← citeshttps://doi.org/10.1186/s12859-020-03708-xopenalex-snapshot
BITS2019: the sixteenth annual meeting of the Italian society of bioinformatics
inferred← citeshttps://doi.org/10.1186/s13321-016-0162-2openalex-snapshot
Computational methods for prediction of in vitro effects of new chemical structures
inferred← citeshttps://doi.org/10.1186/s13321-017-0215-1openalex-snapshot
ChemSAR: an online pipelining platform for molecular SAR modeling
inferred← citeshttps://doi.org/10.1186/s13321-017-0256-5openalex-snapshot
An automated framework for QSAR model building
inferred← citeshttps://doi.org/10.1186/s13321-018-0270-2openalex-snapshot
PyBioMed: a python library for various molecular representations of chemicals, proteins and DNAs and their interactions
inferred← citeshttps://doi.org/10.1186/s13321-018-0300-0openalex-snapshot
Exploring non-linear distance metrics in the structure–activity space: QSAR models for human estrogen receptor
inferred← citeshttps://doi.org/10.1186/s13321-019-0356-5openalex-snapshot
Leveraging heterogeneous data from GHS toxicity annotations, molecular and protein target descriptors and Tox21 assay readouts to predict and rationalise acute toxicity
inferred← citeshttps://doi.org/10.1186/s13321-019-0396-xopenalex-snapshot
Efficient learning of non-autoregressive graph variational autoencoders for molecular graph generation
inferred← citeshttps://doi.org/10.1186/s13321-020-00426-7openalex-snapshot
Predicting liver cytosol stability of small molecules
inferred← citeshttps://doi.org/10.1186/s13321-021-00510-6openalex-snapshot
Multi-PLI: interpretable multi‐task deep learning model for unifying protein–ligand interaction datasets
inferred← citeshttps://doi.org/10.1186/s13321-025-00989-3openalex-snapshot
Enhancing molecular property prediction with quantized GNN models
inferred← citeshttps://doi.org/10.13005/ojc/420110openalex-snapshot
Prediction of new ESIPT Molecules by Machine Learning and Quantum Modelling
inferred← citeshttps://doi.org/10.1371/journal.pone.0073587openalex-snapshot
In Silico Mechanistic Profiling to Probe Small Molecule Binding to Sulfotransferases
inferred← citeshttps://doi.org/10.1371/journal.pone.0119301openalex-snapshot
Systematic Artifacts in Support Vector Regression-Based Compound Potency Prediction Revealed by Statistical and Activity Landscape Analysis
inferred← citeshttps://doi.org/10.1371/journal.pone.0282924openalex-snapshot
Guidance for good practice in the application of machine learning in development of toxicological quantitative structure-activity relationships (QSARs)
inferred← citeshttps://doi.org/10.1515/jib-2018-0065openalex-snapshot
Deep Convolutional Neural Networks for the Prediction of Molecular Properties: Challenges and Opportunities Connected to the Data
inferred← citeshttps://doi.org/10.1515/psr-2018-0115openalex-snapshot
Prediction of modes of action of components of traditional medicinal preparations
inferred← citeshttps://doi.org/10.1517/17460441.2016.1146250openalex-snapshot
Use of machine learning approaches for novel drug discovery
inferred← citeshttps://doi.org/10.17863/cam.36962openalex-snapshot
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