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A deep learning framework for improving protein interaction prediction using sequence properties

Authors: Xiang Chen;

A deep learning framework for improving protein interaction prediction using sequence properties

Abstract

Protein-protein interactions (PPIs) are central to most biological processes. Although efforts have been devoted to the development of a methodology for predicting PPIs and protein interaction networks, the application of most existing methods is limited because they need information about protein homology or the interaction marks of the protein partners. In the present work, we propose a method for PPI prediction using only the property of protein sequences. This method was developed based on a deep learning framework combined with a K-means-based conjoint triad feature for describing protein sequences. The prediction ability of our approach is better than that of other sequence-based PPI prediction methods.

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Keywords

Properties of protein sequence, Protein-protein interactions, Deep learning framework

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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