Comparison of Target Features for Predicting Drug-Target Interactions by Deep Neural Network Based on Large-Scale Drug-Induced Transcriptome Data

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Predicting Parkinson's Disease Genes Based on Node2vec and Autoencoder

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Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations

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OUP accepted manuscript

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Computational prediction of drug–target interactions using chemogenomic approaches: an empirical survey

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OUP accepted manuscript

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Brain-specific functional relationship networks inform autism spectrum disorder gene prediction

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Deep learning-based transcriptome data classification for drug-target interaction prediction

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Machine Learning for Drug-Target Interaction Prediction

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Deep learning for biology

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Deep-Learning-Based Drug–Target Interaction Prediction

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Elucidating the modes of action for bioactive compounds in a cell-specific manner by large-scale chemically-induced transcriptomics

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The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible

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KEGG: new perspectives on genomes, pathways, diseases and drugs

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Drug Repositioning for Cancer Therapy Based on Large-Scale Drug-Induced Transcriptional Signatures

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Predicting target proteins for drug candidate compounds based on drug-induced gene expression data in a chemical structure-independent manner

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Drug–target interaction prediction: databases, web servers and computational models

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Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

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Predicting effects of noncoding variants with deep learning–based sequence model

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ChEMBL web services: streamlining access to drug discovery data and utilities

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Connectivity Map-based discovery of parbendazole reveals targetable human osteogenic pathway

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Drug target prioritization by perturbed gene expression and network information

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The Molecular Signatures Database Hallmark Gene Set Collection

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Gene Ontology and KEGG Pathway Enrichment Analysis of a Drug Target-Based Classification System

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Novel Drug Candidates for the Treatment of Metastatic Colorectal Cancer through Global Inverse Gene-Expression Profiling

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Structure-Based Virtual Screening for Drug Discovery: Principles, Applications and Recent Advances

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Recent improvements to Binding MOAD: a resource for protein–ligand binding affinities and structures

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Similarity-based machine learning methods for predicting drug–target interactions: a brief review

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DrugBank 4.0: shedding new light on drug metabolism

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Correction: Prediction of Drug-Target Interactions for Drug Repositioning Only Based on Genomic Expression Similarity

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IUPHAR-DB: updated database content and new features

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The Comparative Toxicogenomics Database: update 2013

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State-of-the-art in ligand-based virtual screening

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Discovery of drug mode of action and drug repositioning from transcriptional responses

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Network pharmacology: the next paradigm in drug discovery

(2008) Andrew L Hopkins   Nature Chemical Biology