Research graph
References from Drug-induced liver injury prediction based on graph convolutional networks and toxicogenomics. Local targets link to admitted publications; unresolved targets remain external evidence.
Drug-induced liver disorders: implications for drug development and regulation
10.2165/00002018-200124070-00001 · 2001 · External reference
Drug induced liver injury: an update
10.1007/s00204-020-02885-1 · 2020 · External reference
Drug Withdrawal Due to Safety: A Review of the Data Supporting Withdrawal Decision
10.2174/1574886314666191004092520 · 2020 · External reference
How to improve R&D productivity: the pharmaceutical industry’s grand challenge
10.1038/nrd3078 · 2010 · External reference
Mixed learning algorithms and features ensemble in hepatotoxicity prediction
10.1007/s10822-011-9468-3 · 2011 · External reference
Predicting drug-induced liver injury using ensemble learning methods and molecular fingerprints
10.1093/toxsci/kfy121 · 2018 · External reference
Deep learning for drug-induced liver injury
10.1021/acs.jcim.5b00238 · 2015 · External reference
ResNet18DNN: prediction approach of drug-induced liver injury by deep neural network with ResNet18
10.1093/bib/bbab503 · 2022 · External reference
Drug–target affinity prediction using rotary encoding and information retention mechanisms
10.1016/j.engappai.2025.110239 · 2025 · External reference
Associative learning mechanism for drug-target interaction prediction
10.1049/cit2.12194 · 2023 · External reference
Toxicogenomics in drug discovery and development: mechanistic analysis of compound/class-dependent effects using the DrugMatrix database
10.2217/14622416.7.7.1025 · 2006 · External reference
Open TG-GATEs: a large-scale toxicogenomics database
10.1093/nar/gku955 · 2015 · External reference
A next generation connectivity map: L1000 platform and the first 1,000,000 profiles
10.1016/j.cell.2017.10.049 · 2017 · External reference
DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans
10.1016/j.drudis.2016.02.015 · 2016 · External reference
Computational models using multiple machine learning algorithms for predicting drug hepatotoxicity with the DILIrank dataset
10.3390/ijms21062114 · 2020 · External reference
Comparing machine learning algorithms for predicting Drug-Induced Liver Injury (DILI)
10.1021/acs.molpharmaceut.0c00326 · 2020 · External reference
Drug-induced liver injury in critically ill children taking antiepileptic drugs: a retrospective study
10.1016/j.curtheres.2020.100580 · 2020 · External reference
Drug-induced liver injury severity and toxicity (DILIst): binary classification of 1279 drugs by human hepatotoxicity
10.1016/j.drudis.2019.09.022 · 2020 · External reference
Deep learning on high-throughput transcriptomics to predict drug-induced liver injury
10.3389/fbioe.2020.562677 · 2020 · External reference
Semi-supervised classification with graph convolutional networks
2017 · External reference
Deep learning in bioinformatics: introduction, application, and perspective in the big data era
10.1016/j.ymeth.2019.04.008 · 2019 · External reference
Modeling polypharmacy side effects with graph convolutional networks
10.1093/bioinformatics/bty294 · 2018 · External reference
Towards probabilistic generative models harnessing graph neural networks for disease-gene prediction
2019 · External reference
Drug–target binding affinity prediction model based on multi-scale diffusion and interactive learning
10.1016/j.eswa.2024.124647 · 2024 · External reference
Drug-target affinity prediction method based on multi-scale information interaction and graph optimization
10.1016/j.compbiomed.2023.107621 · 2023 · External reference
A tutorial on spectral clustering
10.1007/s11222-007-9033-z · 2007 · External reference
Graph learning-convolutional networks
2018 · External reference
Distant metastasis identification based on optimized graph representation of gene interaction patterns
2022 · External reference
Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics
10.1093/bib/bbae673 · 2024 · External reference
ToxGIN: an In silico prediction model for peptide toxicity via graph isomorphism networks integrating peptide sequence and structure information
2024 · External reference
p53 attenuates acetaminophen-induced hepatotoxicity by regulating drug-metabolizing enzymes and transporter expression
10.1038/s41419-018-0507-z · 2018 · External reference
Hepatospecific ablation of p38α MAPK governs liver regeneration through modulation of inflammatory response to CCl4-induced acute injury
10.1038/s41598-019-51175-z · 2019 · External reference
G protein β5-ATM complexes drive acetaminophen-induced hepatotoxicity
10.1016/j.redox.2021.101965 · 2021 · External reference
Smad phosphoisoform signals in acute and chronic liver injury: similarities and differences between epithelial and mesenchymal cells
10.1007/s00441-011-1178-6 · 2012 · External reference
An integrated biomimetic array chip for establishment of collagen-based 3D primary human hepatocyte model for prediction of clinical drug-induced liver injury
10.1002/bit.27931 · 2021 · External reference
ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader cover- age, improved performance, API functionality and decision support
2024 · External reference
Drug Induced Liver Injury (DILI). Mechanisms and medicinal chemistry avoidance/mitigation strategies
10.1021/acs.jmedchem.0c00524 · 2020 · External reference
Predicting drug-induced hepatotoxicity based on biological feature maps and diverse classification strategies
10.1093/bib/bbz165 · 2021 · External reference
Gene ontology: tool for the unification of biology. The Gene Ontology Consortium
10.1038/75556 · 2000 · External reference
Evaluating protein-protein interaction (PPI) networks for diseases pathway, target discovery, and drug-design using “in silico pharmacology”
10.2174/1389203715666140724090153 · 2014 · External reference
The STRING database in 2021 : customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets
10.1093/nar/gkab835 · 2021 · External reference
Exploring pharmacological active ingredients of traditional Chinese medicine by pharmacotranscriptomic map in ITCM
10.1093/bib/bbad027 · 2023 · External reference
