Attention mechanism enhanced LSTM with residual architecture and its application for protein-protein interaction residue pairs prediction

Attention mechanism enhanced LSTM with residual architecture and its application for protein-protein interaction residue pairs prediction

Abstract Background Recurrent neural network(RNN) is a good way to process sequential data, but the capability of RNN to compute long sequence data is inefficient. As a variant of RNN, long short term memory(LSTM) solved the problem in some extent. Here we improved LSTM for big data application in p...

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Bibliographic Details
Main Authors: Jiale Liu, Xinqi Gong
Format: Article
Language:English
Published: BMC 2019-11-01
Series:BMC Bioinformatics
Subjects:
Residual architecture
Attention
LSTM
Protein-protein interaction prediction
Monte Carlo
Online Access:http://link.springer.com/article/10.1186/s12859-019-3199-1

Internet

http://link.springer.com/article/10.1186/s12859-019-3199-1

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