Compound–protein interaction prediction with end-to-end learning of neural networks for graphs and sequences-Reference-Cited by-同舟云学术

Compound–protein interaction prediction with end-to-end learning of neural networks for graphs and sequences

Published:2018-07-06 Issue:2 Volume:35 Page:309-318
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Tsubaki Masashi¹,Tomii Kentaro¹²,Sese Jun¹²

Affiliation:

1. National Institute of Advanced Industrial Science and Technology, Artificial Intelligence Research Center, Tokyo, Japan

2. AIST- Tokyo Tech Real World Big-Data Computation Open Innovation Laboratory, Tokyo, Japan

Funder

NEDO

JSPS KAKENHI

Platform Project for Supporting Drug Discovery and Life Science Research

Basis for Supporting Innovative Drug Discovery and Life Science Research

BINDS

AMED

JST CREST

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/35/2/309/27497010/bty535.pdf

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4. Prediction of chemical–protein interactions: multitarget-qsar versus computational chemogenomic methods;Cheng;Mol. BioSyst,2012

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