Computational Prediction of DrugTarget Interactions Using Chemical, Biological, and Network Features (Q30391368)

21 June 2017

Computational Prediction of DrugTarget Interactions Using Chemical, Biological, and Network Features (English)

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21 June 2017

computational biology

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author name string

Dong-Sheng Cao

1

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21 June 2017

Liu-Xia Zhang

2

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21 June 2017

Gui-Shan Tan

3

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21 June 2017

Zheng Xiang

4

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21 June 2017

Wen-Bin Zeng

5

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21 June 2017

Qing-Song Xu

6

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21 June 2017

Alex F Chen

7

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21 June 2017

26 September 2014

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21 June 2017

Molecular Informatics

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21 June 2017

33

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21 June 2017

669-681

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21 June 2017

10

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Target-drug interactions: first principles and their application to drug discovery

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Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework

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Drug repositioning: identifying and developing new uses for existing drugs

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Trends in the exploitation of novel drug targets

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Network pharmacology: the next paradigm in drug discovery

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Network biology: understanding the cell's functional organization

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Global mapping of pharmacological space

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Large-scale prediction of drug-target relationships

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DrugBank: a comprehensive resource for in silico drug discovery and exploration

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An overview of the PubChem BioAssay resource

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BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities

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Using entropy of drug and protein graphs to predict FDA drug-target network: theoretic-experimental study of MAO inhibitors and hemoglobin peptides from Fasciola hepatica.

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Relating protein pharmacology by ligand chemistry

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Drug target identification using side-effect similarity

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Chemogenomics: structuring the drug discovery process to gene families.

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Large-scale prediction of drug-target interactions using protein sequences and drug topological structures.

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2D MI-DRAGON: a new predictor for protein-ligands interactions and theoretic-experimental studies of US FDA drug-target network, oxoisoaporphine inhibitors for MAO-A and human parasite proteins.

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Supervised prediction of drug-target interactions using bipartite local models

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Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces.

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Protein-ligand interaction prediction: an improved chemogenomics approach.

21 January 2018

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Statistical prediction of protein chemical interactions based on chemical structure and mass spectrometry data

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Predicting drug-target interaction networks based on functional groups and biological features

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Gaussian interaction profile kernels for predicting drug-target interaction.

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A systematic prediction of multiple drug-target interactions from chemical, genomic, and pharmacological data

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Relating drug-protein interaction network with drug side effects

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Prediction of chemical-protein interactions network with weighted network-based inference method

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Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs

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Data-driven prediction of drug effects and interactions

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Prediction of drug-target interaction networks from the integration of chemical and genomic spaces.

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In silico classification of human maximum recommended daily dose based on modified random forest and substructure fingerprint.

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Prediction of protein folding class using global description of amino acid sequence

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AAindex: amino acid index database

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KEGG: Kyoto Encyclopedia of Genes and Genomes

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Genome-scale screening of drug-target associations relevant to Ki using a chemogenomics approach

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Chemogenomics: an emerging strategy for rapid target and drug discovery

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Chemogenomic approaches to rational drug design

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Identifiers

DOI

10.1002/MINF.201400009

1 reference

21 June 2017

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