Research graph
References from Artificial intelligence, network biology and multiomics data in drug discovery. Local targets link to admitted publications; unresolved targets remain external evidence.
The role of AI in drug discovery
10.1002/cbic.202300816 · 2024 · External reference
Accurate structure prediction of biomolecular interactions with AlphaFold 3
10.1038/s41586-024-07487-w · 2024 · External reference
Computational approaches for network-based integrative multi-omics analysis
10.3389/fmolb.2022.967205 · 2022 · External reference
Revolutionizing healthcare: the role of artificial intelligence in clinical practice
10.1186/s12909-023-04698-z · 2023 · External reference
Novel drug-target interactions via link prediction and network embedding
10.1186/s12859-022-04650-w · 2022 · External reference
Prediction of effective drug combinations by an improved naïve Bayesian algorithm
10.3390/ijms19020467 · 2018 · External reference
t-SNE based visualisation and clustering of geological domain
2016 · External reference
A clustering and graph deep learning-based framework for COVID-19 drug repurposing
10.1016/j.eswa.2024.123560 · 2024 · External reference
Network medicine: a network-based approach to human disease
10.1038/nrg2918 · 2011 · External reference
A review on graph neural networks for predicting synergistic drug combinations
10.1007/s10462-023-10669-z · 2024 · External reference
COMO: a pipeline for multi-omics data integration in metabolic modeling and drug discovery
10.1093/bib/bbad387 · 2023 · External reference
Mass spectrometry-based proteomics as an emerging tool in clinical laboratories
10.1186/s12014-023-09424-x · 2023 · External reference
Application of generative autoencoder in de novo molecular design
2018 · External reference
Interpretation of network-based integration from multi-omics longitudinal data
10.1093/nar/gkab1200 · 2022 · External reference
Glycoinformatics in the artificial intelligence era
10.1021/acs.chemrev.2c00110 · 2022 · External reference
DNN-DTIs: improved drug-target interactions prediction using XGBoost feature selection and deep neural network
10.1016/j.compbiomed.2021.104676 · 2021 · External reference
The rise of deep learning in drug discovery
10.1016/j.drudis.2018.01.039 · 2018 · External reference
Construction and analysis of protein-protein interaction network of heroin use disorder
2019 · External reference
Artificial intelligence for drug discovery: resources, methods, and applications
10.1016/j.omtn.2023.02.019 · 2023 · External reference
Plasma lipidomics profiling identified lipid biomarkers in distinguishing early-stage breast cancer from benign lesions
10.18632/oncotarget.9124 · 2016 · External reference
Chapter 5: network biology approach to complex diseases
10.1371/journal.pcbi.1002820 · 2012 · External reference
De novo drug design through artificial intelligence: an introduction
10.3389/frhem.2024.1305741 · 2024 · External reference
Advances and trends in omics technology development
10.3389/fmed.2022.911861 · 2022 · External reference
Machine learning in drug discovery: a review
10.1007/s10462-021-10058-4 · 2022 · External reference
MolGAN: an implicit generative model for small molecular graphs
2018 · External reference
Immunomics: a 21st century approach to vaccine development for complex pathogens
10.1017/s0031182015001079 · 2016 · External reference
Mergeomics 2.0: a web server for multi-omics data integration to elucidate disease networks and predict therapeutics
10.1093/nar/gkab405 · 2021 · External reference
Advances in integrated multi-omics analysis for drug-target identification
10.3390/biom14060692 · 2024 · External reference
MasitinibL shows promise as a drug-like analog of masitinib that elicits comparable SARS-Cov-2 3CLpro inhibition with low kinase preference
10.1038/s41598-023-33024-2 · 2023 · External reference
Exploiting machine learning for end-to-end drug discovery and development
10.1038/s41563-019-0338-z · 2019 · External reference
GCRNN: graph convolutional recurrent neural network for compound–protein interaction prediction
10.1186/s12859-022-04560-x · 2021 · External reference
A guide to deep learning in healthcare
10.1038/s41591-018-0316-z · 2019 · External reference
Whole exome and genome sequencing in mendelian disorders: a diagnostic and health economic analysis
10.1038/s41431-022-01162-2 · 2022 · External reference
Revolutionizing drug discovery: an AI-powered transformation of molecular docking
10.1007/s00044-024-03253-9 · 2024 · External reference
Can artificial intelligence accelerate preclinical drug discovery and precision medicine?
10.1080/17460441.2022.2090540 · 2022 · External reference
Drugging the epigenome in the age of precision medicine
10.1186/s13148-022-01419-z · 2023 · External reference
Immunomics in one health: understanding the human, animal, and environmental aspects of COVID-19
10.3389/fimmu.2024.1450380 · 2024 · External reference
Metabolomics paves the way for improved drug target identification
10.15252/msb.202210914 · 2022 · External reference
Democratized image analytics by visual programming through integration of deep models and small-scale machine learning
10.1038/s41467-019-12397-x · 2019 · External reference
SMILES2vec: an interpretable general-purpose deep neural network for predicting chemical properties
2017 · External reference
Objective-reinforced generative adversarial networks (ORGAN) for sequence generation models
2017 · External reference
Big data: an optimized approach for cluster initialization
10.1186/s40537-023-00798-1 · 2023 · External reference
Feedback GAN for DNA optimizes protein functions
10.1038/s42256-019-0017-4 · 2019 · External reference
Artificial intelligence to deep learning: machine intelligence approach for drug discovery
10.1007/s11030-021-10217-3 · 2021 · External reference
Biological omics databases and tools
2024 · External reference
Lipid alterations in the earliest clinically recognizable stage of Alzheimers disease: implication of the role of lipids in the pathogenesis of Alzheimers disease
10.2174/1567205052772786 · 2005 · External reference
Network-based approaches in drug discovery and early development
10.1038/clpt.2013.176 · 2013 · External reference
Multi-omics approaches to disease
10.1186/s13059-017-1215-1 · 2017 · External reference
KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species
10.1111/pbi.13583 · 2021 · External reference
10.1016/j.scib.2025.10.002
10.1016/j.scib.2025.10.002 · External reference
Proteomics approaches for biomarker and drug target discovery in als and ftd
10.3389/fnins.2019.00548 · 2019 · External reference
Galaxy training: a powerful framework for teaching!
10.1371/journal.pcbi.1010752 · 2023 · External reference
ScaffoldGVAE: scaffold generation and hopping of drug molecules via a variational autoencoder based on multi-view graph neural networks
10.1186/s13321-023-00766-0 · 2023 · External reference
DeepPurpose: a deep learning library for drug-target interaction prediction
10.1093/bioinformatics/btaa1005 · 2020 · External reference
Dimensionality reduction for knowledge discovery in medical claims database: application to antidepressant medication utilization study
10.1016/j.cmpb.2008.08.002 · 2009 · External reference
Computer-aided screening for potential TMPRSS2 inhibitors: a combination of pharmacophore modeling, molecular docking and molecular dynamics simulation approaches
2020 · External reference
Epigenomics and Interindividual differences in drug response
10.1038/clpt.2012.152 · 2012 · External reference
Approaches for network based drug discovery
10.52586/s551 · 2021 · External reference
Prediction of protein–protein interaction using graph neural networks
10.1038/s41598-022-12201-9 · 2022 · External reference
Proteomics in drug discovery
2012 · External reference
Artificial intelligence in healthcare: past, present and future
10.1136/svn-2017-000101 · 2017 · External reference
Network-based multi-omics integrative analysis methods in drug discovery: a systematic review
10.1186/s13040-025-00442-z · 2025 · External reference
Tox_(R)CNN: deep learning-based nuclei profiling tool for drug toxicity screening
10.1371/journal.pcbi.1006238 · 2018 · External reference
10.20944/preprints202408.0350.v1
10.20944/preprints202408.0350.v1 · External reference
Metabolomics: beyond biomarkers and towards mechanisms
10.1038/nrm.2016.25 · 2016 · External reference
KNIME workflows for applications in medicinal and computational chemistry
10.1016/j.aichem.2024.100063 · 2024 · External reference
Solving Newton’s equations of motion with large timesteps using recurrent neural networks based operators
10.1088/2632-2153/ac5f60 · 2022 · External reference
PandaOmics: an AI-driven platform for therapeutic target and biomarker discovery
10.1021/acs.jcim.3c01619 · 2024 · External reference
Computational approaches in target identification and drug discovery
10.1016/j.csbj.2016.04.004 · 2016 · External reference
Predicting biomedical interactions with higher-order graph convolutional networks
10.1109/tcbb.2021.3059415 · 2022 · External reference
Dynamics and sensitivity of signaling pathways
10.1007/s40139-022-00230-y · 2022 · External reference
DeepConv-DTI: prediction of drug-target interactions via deep learning with convolution on protein sequences
10.1371/journal.pcbi.1007129 · 2019 · External reference
PepGB: facilitating peptide drug discovery via graph neural networks
2024 · External reference
CSER: a gene regulatory network construction method based on causal strength and ensemble regression
10.3389/fgene.2024.1481787 · 2024 · External reference
Application of artificial intelligence in drug-target interactions prediction: a review
10.1038/s44385-024-00003-9 · 2025 · External reference
Chemi-Net: a molecular graph convolutional network for accurate drug property prediction
10.3390/ijms20143389 · 2019 · External reference
Reinvent 4: modern AI–driven generative molecule design
10.1186/s13321-024-00812-5 · 2024 · External reference
Transcriptomics technologies
10.1371/journal.pcbi.1005457 · 2017 · External reference
Multi-layer graph attention neural networks for accurate drug-target interaction mapping
2024 · External reference
GenoCraft: a comprehensive, user-friendly web-based platform for high-throughput omics data analysis and visualization
2023 · External reference
A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information
10.1038/s41467-017-00680-8 · 2017 · External reference
A guide to machine learning for bacterial host attribution using genome sequence data
10.1099/mgen.0.000317 · 2019 · External reference
Single-cell multiomics: a new frontier in drug research and development
10.3389/fddsv.2024.1474331 · 2024 · External reference
MedGAN: optimized generative adversarial network with graph convolutional networks for novel molecule design
10.1038/s41598-023-50834-6 · 2024 · External reference
Artificial intelligence in drug development: present status and future prospects
10.1016/j.drudis.2018.11.014 · 2019 · External reference
The role of AI in hospitals and clinics: transforming healthcare in the 21st century
10.3390/bioengineering11040337 · 2024 · External reference
Evaluation of featurizer-model combinations and their interpretability in toxicity prediction
10.61463/ijset.vol.12.issue6.359 · 2024 · External reference
Should network biology be used for drug discovery?
10.1080/17460441.2016.1236786 · 2016 · External reference
alvaDesc: a tool to calculate and analyze molecular descriptors and fingerprints
10.1007/978-1-0716-0150-1_32 · 2020 · External reference
Mol-CycleGAN: a generative model for molecular optimization
10.1186/s13321-019-0404-1 · 2020 · External reference
A proposal for the Dartmouth summer research project on artificial intelligence
2006 · External reference
Lipidomics: potential role in risk prediction and therapeutic monitoring for diabetes and cardiovascular disease
10.1016/j.pharmthera.2014.02.001 · 2014 · External reference
Introduction to artificial intelligence in medicine
10.1080/13645706.2019.1575882 · 2019 · External reference
From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies
10.1007/s12033-024-01133-6 · 2024 · External reference
Bioactive molecule prediction using extreme gradient boosting
10.3390/molecules21080983 · 2016 · External reference
New insights into protein–protein interaction modulators in drug discovery and therapeutic advance
10.1038/s41392-024-02036-3 · 2024 · External reference
A review of computational methods for clustering genes with similar biological functions
10.3390/pr7090550 · 2019 · External reference
Integrating artificial intelligence in drug discovery and early drug development: a transformative approach
10.1186/s40364-025-00758-2 · 2025 · External reference
Variational autoencoder-based chemical latent space for large molecular structures with 3D complexity
10.1038/s42004-023-01054-6 · 2023 · External reference
Glycomics in human diseases and its emerging role in biomarker discovery
10.3390/biomedicines13082034 · 2025 · External reference
The molecular twin artificial-intelligence platform integrates multi-omic data to predict outcomes for pancreatic adenocarcinoma patients
10.1038/s43018-023-00697-7 · 2024 · External reference
Cytoscape automation: empowering workflow-based network analysis
10.1186/s13059-019-1758-4 · 2019 · External reference
Metabolomics-driven approaches for identifying therapeutic targets in drug discovery
10.1002/mco2.792 · 2024 · External reference
Artificial intelligence in drug discovery and development
10.1016/j.drudis.2020.10.010 · 2021 · External reference
Integration strategies of multi-omics data for machine learning analysis
10.1016/j.csbj.2021.06.030 · 2021 · External reference
Unraveling the molecular repertoire of tears as a source of biomarkers: beyond ocular diseases
10.1002/prca.201400084 · 2015 · External reference
MolecularRNN: generating realistic molecular graphs with optimized properties
2019 · External reference
Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data
10.1038/s41592-019-0690-6 · 2020 · External reference
AI-powered therapeutic target discovery
10.1016/j.tips.2023.06.010 · 2023 · External reference
Human protein–protein interaction networks: a topological comparison review
10.1016/j.heliyon.2024.e27278 · 2024 · External reference
Unresolved reference
External reference
Using machine learning approaches for multi-omics data analysis: a review
10.1016/j.biotechadv.2021.107739 · 2021 · External reference
Application of a kNN ‐based similarity method to biopharmaceutical manufacturing
10.1002/btpr.2945 · 2020 · External reference
De novo prediction of cell-drug sensitivities using deep learning-based graph regularized matrix factorization
2021 · External reference
Nonlinear dimensionality reduction and mapping of compound libraries for drug discovery
10.1016/j.jmgm.2011.12.006 · 2012 · External reference
DEEPScreen: high performance drug-target interaction prediction with convolutional neural networks using 2-D structural compound representations
10.1039/c9sc03414e · 2020 · External reference
Evolution of support vector machine and regression modeling in chemoinformatics and drug discovery
10.1007/s10822-022-00442-9 · 2022 · External reference
Automating drug discovery
10.1038/nrd.2017.232 · 2018 · External reference
Improved protein structure prediction using potentials from deep learning
10.1038/s41586-019-1923-7 · 2020 · External reference
Pocket2Drug: An encoder-decoder deep neural network for the target-based drug design
2022 · External reference
Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure
10.1016/j.ygeno.2018.12.007 · 2019 · External reference
Glycomics: a pathway to a class of new and improved therapeutics
10.1038/nrd1521 · 2004 · External reference
Practical outcomes of applying ensemble machine learning classifiers to high-throughput screening (HTS) data analysis and screening
10.1021/ci800164u · 2008 · External reference
Artificial intelligence, machine learning and deep learning in advanced robotics, a review
10.1016/j.cogr.2023.04.001 · 2023 · External reference
Molecular analysis and design using generative artificial intelligence via multi-agent modeling
10.1039/d4me00174e · 2025 · External reference
Multi-omics data integration, interpretation, and its application
10.1177/1177932219899051 · 2020 · External reference
Autoencoder-based drug-target interaction prediction by preserving the consistency of chemical properties and functions of drugs
10.1093/bioinformatics/btab384 · 2021 · External reference
Deciphering signaling pathway networks to understand the molecular mechanisms of metformin action
10.1371/journal.pcbi.1004202 · 2015 · External reference
Editorial: bioinformatics analysis of omics data for biomarker identification in clinical research, Volume II
10.3389/fgene.2023.1256468 · 2023 · External reference
A review on analysis of K-means clustering machine learning algorithm based on unsupervised learning
2024 · External reference
Random Forest: a classification and regression tool for compound classification and QSAR modeling
10.1021/ci034160g · 2003 · External reference
Analysis of the uncharted, druglike property space by self-organizing maps
10.1007/s11030-021-10343-y · 2022 · External reference
Clustering of small molecules: new perspectives and their impact on natural product lead discovery
10.3389/fntpr.2024.1367537 · 2024 · External reference
Machine learning for pharmacokinetic/pharmacodynamic modeling
10.1016/j.xphs.2023.01.010 · 2023 · External reference
Molecular generative adversarial network with multi-property optimization
2024 · External reference
Auxiliary discrminator sequence generative adversarial networks (ADSeqGAN) for few sample molecule generation
2025 · External reference
10.1101/2024.11.08.622488
10.1101/2024.11.08.622488 · External reference
Recent advances and application of generative adversarial networks in drug discovery, development, and targeting
10.1016/j.ailsci.2022.100045 · 2022 · External reference
Gene regulatory networks in disease and ageing
10.1038/s41581-024-00849-7 · 2024 · External reference
Applications of machine learning in drug discovery and development
10.1038/s41573-019-0024-5 · 2019 · External reference
Unresolved reference
External reference
Network-based integration of multi-omics data for clinical outcome prediction in neuroblastoma
2022 · External reference
Deep learning and multi-omics approach to predict drug responses in cancer
2021 · External reference
Epigenomics technologies and applications
10.1161/circresaha.118.310998 · 2018 · External reference
ADME properties evaluation in drug discovery: prediction of Caco-2 cell permeability using a combination of NSGA-II and boosting
10.1021/acs.jcim.5b00642 · 2016 · External reference
Applications of metabolomics in drug discovery and development
10.2165/00126839-200809050-00002 · 2008 · External reference
LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters
10.1021/ci049885e · 2005 · External reference
Network-based methods for prediction of drug-target interactions
10.3389/fphar.2018.01134 · 2018 · External reference
Application of machine learning for drug–target interaction prediction
2021 · External reference
Biomolecular networks
2024 · External reference
Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data
2017 · External reference
Lipidomics: techniques, applications, and outcomes related to biomedical sciences
10.1016/j.tibs.2016.08.010 · 2016 · External reference
High-throughput transcriptome profiling in drug and biomarker discovery
2020 · External reference
GraphRNN: generating realistic graphs with deep auto-regressive models
2018 · External reference
Artificial intelligence in cancer target identification and drug discovery
10.1038/s41392-022-00994-0 · 2022 · External reference
Integrative analysis of omics big data
10.1007/978-1-4939-7717-8_7 · 2018 · External reference
Integrative clustering methods for multi-omics data
10.1002/wics.1553 · 2022 · External reference
Drug-target interaction prediction by integrating heterogeneous information with mutual attention network
2024 · External reference
Deep learning driven drug discovery: Tackling severe acute respiratory syndrome coronavirus 2
2021 · External reference
OmicsNet 2.0: a web-based platform for multi-omics integration and network visual analytics
10.1093/nar/gkac376 · 2022 · External reference
AlzGPS: a genome-wide positioning systems platform to catalyze multi-omics for Alzheimer’s drug discovery
10.1186/s13195-020-00760-w · 2021 · External reference
Metascape provides a biologist-oriented resource for the analysis of systems-level datasets
2019 · External reference
Application of pharmacokinetic-pharmacodynamic modeling in drug delivery: development and challenges
10.3389/fphar.2020.00997 · 2020 · External reference
Application of a kNN ‐based similarity method to biopharmaceutical manufacturing
10.1002/btpr.2945 · ExternalCitation · doi-reference
The role of AI in drug discovery
10.1002/cbic.202300816 · ExternalCitation · doi-reference
Metabolomics-driven approaches for identifying therapeutic targets in drug discovery
10.1002/mco2.792 · ExternalCitation · doi-reference
Unraveling the molecular repertoire of tears as a source of biomarkers: beyond ocular diseases
10.1002/prca.201400084 · ExternalCitation · doi-reference
Integrative clustering methods for multi-omics data
10.1002/wics.1553 · ExternalCitation · doi-reference
alvaDesc: a tool to calculate and analyze molecular descriptors and fingerprints
10.1007/978-1-0716-0150-1_32 · ExternalCitation · doi-reference
Integrative analysis of omics big data
10.1007/978-1-4939-7717-8_7 · ExternalCitation · doi-reference
Revolutionizing drug discovery: an AI-powered transformation of molecular docking
10.1007/s00044-024-03253-9 · ExternalCitation · doi-reference
Machine learning in drug discovery: a review
10.1007/s10462-021-10058-4 · ExternalCitation · doi-reference
A review on graph neural networks for predicting synergistic drug combinations
10.1007/s10462-023-10669-z · ExternalCitation · doi-reference
Evolution of support vector machine and regression modeling in chemoinformatics and drug discovery
10.1007/s10822-022-00442-9 · ExternalCitation · doi-reference
Artificial intelligence to deep learning: machine intelligence approach for drug discovery
10.1007/s11030-021-10217-3 · ExternalCitation · doi-reference
Analysis of the uncharted, druglike property space by self-organizing maps
10.1007/s11030-021-10343-y · ExternalCitation · doi-reference
From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies
10.1007/s12033-024-01133-6 · ExternalCitation · doi-reference
Dynamics and sensitivity of signaling pathways
10.1007/s40139-022-00230-y · ExternalCitation · doi-reference
KNIME workflows for applications in medicinal and computational chemistry
10.1016/j.aichem.2024.100063 · ExternalCitation · doi-reference
Recent advances and application of generative adversarial networks in drug discovery, development, and targeting
10.1016/j.ailsci.2022.100045 · ExternalCitation · doi-reference
Using machine learning approaches for multi-omics data analysis: a review
10.1016/j.biotechadv.2021.107739 · ExternalCitation · doi-reference
Dimensionality reduction for knowledge discovery in medical claims database: application to antidepressant medication utilization study
10.1016/j.cmpb.2008.08.002 · ExternalCitation · doi-reference
Artificial intelligence, machine learning and deep learning in advanced robotics, a review
10.1016/j.cogr.2023.04.001 · ExternalCitation · doi-reference
DNN-DTIs: improved drug-target interactions prediction using XGBoost feature selection and deep neural network
10.1016/j.compbiomed.2021.104676 · ExternalCitation · doi-reference
Computational approaches in target identification and drug discovery
10.1016/j.csbj.2016.04.004 · ExternalCitation · doi-reference
Integration strategies of multi-omics data for machine learning analysis
10.1016/j.csbj.2021.06.030 · ExternalCitation · doi-reference
The rise of deep learning in drug discovery
10.1016/j.drudis.2018.01.039 · ExternalCitation · doi-reference
Artificial intelligence in drug development: present status and future prospects
10.1016/j.drudis.2018.11.014 · ExternalCitation · doi-reference
Artificial intelligence in drug discovery and development
10.1016/j.drudis.2020.10.010 · ExternalCitation · doi-reference
A clustering and graph deep learning-based framework for COVID-19 drug repurposing
10.1016/j.eswa.2024.123560 · ExternalCitation · doi-reference
Human protein–protein interaction networks: a topological comparison review
10.1016/j.heliyon.2024.e27278 · ExternalCitation · doi-reference
Nonlinear dimensionality reduction and mapping of compound libraries for drug discovery
10.1016/j.jmgm.2011.12.006 · ExternalCitation · doi-reference
Artificial intelligence for drug discovery: resources, methods, and applications
10.1016/j.omtn.2023.02.019 · ExternalCitation · doi-reference
Lipidomics: potential role in risk prediction and therapeutic monitoring for diabetes and cardiovascular disease
10.1016/j.pharmthera.2014.02.001 · ExternalCitation · doi-reference
10.1016/j.scib.2025.10.002
10.1016/j.scib.2025.10.002 · ExternalCitation · doi-reference
Lipidomics: techniques, applications, and outcomes related to biomedical sciences
10.1016/j.tibs.2016.08.010 · ExternalCitation · doi-reference
AI-powered therapeutic target discovery
10.1016/j.tips.2023.06.010 · ExternalCitation · doi-reference
Machine learning for pharmacokinetic/pharmacodynamic modeling
10.1016/j.xphs.2023.01.010 · ExternalCitation · doi-reference
Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure
10.1016/j.ygeno.2018.12.007 · ExternalCitation · doi-reference
Immunomics: a 21st century approach to vaccine development for complex pathogens
10.1017/s0031182015001079 · ExternalCitation · doi-reference
Glycoinformatics in the artificial intelligence era
10.1021/acs.chemrev.2c00110 · ExternalCitation · doi-reference
PandaOmics: an AI-driven platform for therapeutic target and biomarker discovery
10.1021/acs.jcim.3c01619 · ExternalCitation · doi-reference
ADME properties evaluation in drug discovery: prediction of Caco-2 cell permeability using a combination of NSGA-II and boosting
10.1021/acs.jcim.5b00642 · ExternalCitation · doi-reference
Random Forest: a classification and regression tool for compound classification and QSAR modeling
10.1021/ci034160g · ExternalCitation · doi-reference
LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters
10.1021/ci049885e · ExternalCitation · doi-reference
Practical outcomes of applying ensemble machine learning classifiers to high-throughput screening (HTS) data analysis and screening
10.1021/ci800164u · ExternalCitation · doi-reference
Epigenomics and Interindividual differences in drug response
10.1038/clpt.2012.152 · ExternalCitation · doi-reference
Network-based approaches in drug discovery and early development
10.1038/clpt.2013.176 · ExternalCitation · doi-reference
Automating drug discovery
10.1038/nrd.2017.232 · ExternalCitation · doi-reference
Glycomics: a pathway to a class of new and improved therapeutics
10.1038/nrd1521 · ExternalCitation · doi-reference
Network medicine: a network-based approach to human disease
10.1038/nrg2918 · ExternalCitation · doi-reference
Metabolomics: beyond biomarkers and towards mechanisms
10.1038/nrm.2016.25 · ExternalCitation · doi-reference
Artificial intelligence in cancer target identification and drug discovery
10.1038/s41392-022-00994-0 · ExternalCitation · doi-reference
New insights into protein–protein interaction modulators in drug discovery and therapeutic advance
10.1038/s41392-024-02036-3 · ExternalCitation · doi-reference
Whole exome and genome sequencing in mendelian disorders: a diagnostic and health economic analysis
10.1038/s41431-022-01162-2 · ExternalCitation · doi-reference
A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information
10.1038/s41467-017-00680-8 · ExternalCitation · doi-reference
Democratized image analytics by visual programming through integration of deep models and small-scale machine learning
10.1038/s41467-019-12397-x · ExternalCitation · doi-reference
Exploiting machine learning for end-to-end drug discovery and development
10.1038/s41563-019-0338-z · ExternalCitation · doi-reference
Applications of machine learning in drug discovery and development
10.1038/s41573-019-0024-5 · ExternalCitation · doi-reference
Gene regulatory networks in disease and ageing
10.1038/s41581-024-00849-7 · ExternalCitation · doi-reference
Improved protein structure prediction using potentials from deep learning
10.1038/s41586-019-1923-7 · ExternalCitation · doi-reference
Accurate structure prediction of biomolecular interactions with AlphaFold 3
10.1038/s41586-024-07487-w · ExternalCitation · doi-reference
A guide to deep learning in healthcare
10.1038/s41591-018-0316-z · ExternalCitation · doi-reference
Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data
10.1038/s41592-019-0690-6 · ExternalCitation · doi-reference
Prediction of protein–protein interaction using graph neural networks
10.1038/s41598-022-12201-9 · ExternalCitation · doi-reference
MasitinibL shows promise as a drug-like analog of masitinib that elicits comparable SARS-Cov-2 3CLpro inhibition with low kinase preference
10.1038/s41598-023-33024-2 · ExternalCitation · doi-reference
MedGAN: optimized generative adversarial network with graph convolutional networks for novel molecule design
10.1038/s41598-023-50834-6 · ExternalCitation · doi-reference
Variational autoencoder-based chemical latent space for large molecular structures with 3D complexity
10.1038/s42004-023-01054-6 · ExternalCitation · doi-reference
Feedback GAN for DNA optimizes protein functions
10.1038/s42256-019-0017-4 · ExternalCitation · doi-reference
The molecular twin artificial-intelligence platform integrates multi-omic data to predict outcomes for pancreatic adenocarcinoma patients
10.1038/s43018-023-00697-7 · ExternalCitation · doi-reference
Application of artificial intelligence in drug-target interactions prediction: a review
10.1038/s44385-024-00003-9 · ExternalCitation · doi-reference
DEEPScreen: high performance drug-target interaction prediction with convolutional neural networks using 2-D structural compound representations
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Molecular analysis and design using generative artificial intelligence via multi-agent modeling
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