DrugAI: a multi-view deep learning model for predicting drug–target activating/inhibiting mechanisms

Compound–protein interaction prediction by deep learning: Databases, descriptors and models

(2022) Bing-Xue Du et al.   DRUG DISCOVERY TODAY

MultiDTI: drug–target interaction prediction based on multi-modal representation learning to bridge the gap between new chemical entities and known heterogeneous network

(2021) Deshan Zhou et al.   BIOINFORMATICS

基于生物网络的关系推断原理、方法与应用

(2021) Shao Li et al.   Scientia Sinica Informationis

TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments

(2020) Lifan Chen et al.   BIOINFORMATICS

Celastrol Attenuates Angiotensin II–Induced Cardiac Remodeling by Targeting STAT3

(2020) Shiju Ye et al.   CIRCULATION RESEARCH

MONN: A Multi-objective Neural Network for Predicting Compound-Protein Interactions and Affinities

(2020) Shuya Li et al.   Cell Systems

The Natural Compound Notopterol Binds and Targets JAK2/3 to Ameliorate Inflammation and Arthritis

(2020) Qiong Wang et al.   Cell Reports

The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets

(2020) Damian Szklarczyk et al.   NUCLEIC ACIDS RESEARCH

UniProt: the universal protein knowledgebase in 2021

(2020) et al.   NUCLEIC ACIDS RESEARCH

A Comprehensive Survey on Transfer Learning

(2020) Fuzhen Zhuang et al.   PROCEEDINGS OF THE IEEE

Predicting Drug–Target Interaction Using a Novel Graph Neural Network with 3D Structure-Embedded Graph Representation

(2019) Jaechang Lim et al.   Journal of Chemical Information and Modeling

Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism

(2019) Zhaoping Xiong et al.   JOURNAL OF MEDICINAL CHEMISTRY

Graph Convolutional Neural Networks for Predicting Drug-Target Interactions

(2019) Wen Torng et al.   Journal of Chemical Information and Modeling

A Bayesian machine learning approach for drug target identification using diverse data types

(2019) Neel S. Madhukar et al.   Nature Communications

Chemoproteomics reveals baicalin activates hepatic CPT1 to ameliorate diet-induced obesity and hepatic steatosis

(2018) Jianye Dai et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Predicting inhibitory and activatory drug targets by chemically and genetically perturbed transcriptome signatures

(2018) Ryusuke Sawada et al.   Scientific Reports

ChEMBL: towards direct deposition of bioassay data

(2018) David Mendez et al.   NUCLEIC ACIDS RESEARCH

DrugBank 5.0: a major update to the DrugBank database for 2018

(2017) David S Wishart et al.   NUCLEIC ACIDS RESEARCH

Highly selective inhibition of IMPDH2 provides the basis of antineuroinflammation therapy

(2017) Li-Xi Liao et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information

(2017) Yunan Luo et al.   Nature Communications

Molecular graph convolutions: moving beyond fingerprints

(2016) Steven Kearnes et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

Deep learning

(2015) Yann LeCun et al.   NATURE

Honokiol blocks and reverses cardiac hypertrophy in mice by activating mitochondrial Sirt3

(2015) Vinodkumar B. Pillai et al.   Nature Communications

Predicting drug-target interactions using restricted Boltzmann machines

(2013) Yuhao Wang et al.   BIOINFORMATICS

Target identification and mechanism of action in chemical biology and drug discovery

(2013) Monica Schenone et al.   Nature Chemical Biology

PubChem: a public information system for analyzing bioactivities of small molecules

(2009) Y. Wang et al.   NUCLEIC ACIDS RESEARCH