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Extracting Coevolutionary Features from Protein Sequences for Predicting Protein-Protein Interactions by Lun Hu; Keith C.C. Chan is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Extracting Coevolutionary Features from Protein Sequences for Predicting Protein-Protein Interactions about?

Knowing the ways proteins interact with each other are crucial to our understanding of the functional mechanisms of proteins. It is for this reason that different approaches have been developed in attempts to predict protein-protein interactions (PPIs) computationally. Among them, the sequence-based approaches are preferred to the others as they do not require any information about protein properties to perform their tasks. Instead, most sequence-based approaches make use of feature extraction methods to extract features directly from protein sequences so that for each protein sequence, we can construct a feature vector. The feature vectors of every pair of proteins are then concatenated to form two classes of interacting and non-interacting proteins. The prediction of whether or not two proteins interact with each other is then formulated as a classification problem. How accurate PPI predictions can be made therefore depends on how good the features are that can be extracted from the protein sequences to allow interacting or noninteracting to be best distinguished. To do so, instead of extracting such features from individual protein sequences independently of the other protein in

Who reads Extracting Coevolutionary Features from Protein Sequences for Predicting Protein-Protein Interactions?

Author

Lun Hu; Keith C.C. Chan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Published

2016

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)