Open AccessPredicting protein–protein interactions through sequence-based deep learning
Author(s) -
Somaye Hashemifar,
Behnam Neyshabur,
Aly A. Khan,
Jinbo Xu
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty573
Subject(s) - computer science , artificial intelligence , deep learning , machine learning , convolutional neural network , sequence (biology) , data mining , projection (relational algebra) , algorithm , biology , genetics
High-throughput experimental techniques have produced a large amount of protein-protein interaction (PPI) data, but their coverage is still low and the PPI data is also very noisy. Computational prediction of PPIs can be used to discover new PPIs and identify errors in the experimental PPI data.
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