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Prediction of Protein Dispensability through Integrated Analysis of Multiple-Source High-Throughput Data
BibTeX
@MISC{Chen_predictionof,
author = {Yu Chen and Dong Xu},
title = {Prediction of Protein Dispensability through Integrated Analysis of Multiple-Source High-Throughput Data},
year = {}
}
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Abstract
Protein dispensability is fundamental to understanding of gene function and evolution. It is usually studied at the individual gene phenotype level. Recent advances in generating high-throughput data such as genomic sequence data, protein-protein interaction data, gene-expression data, and growth-rate data of mutants allow us to investigate protein dispensability systematically at the genome scale. In our studies, protein dispensability was represented as a fitness score that was measured by the growth rate of gene-deletion mutants. Through analyses of high-throughput data in yeast Saccharomyces cerevisia, we found that a protein’s dispensability had significant correlations with its evolutionary rate and duplication rate, as well as its connectivity in protein-protein interaction network and gene-expression correlation network. Correspondence analysis also showed such significant dependencies, which imply that the integration of high-throughput data can provide substantial information on protein dispensability. Thus neural network and support vector machines were applied to predict protein dispensability. Our study provides a “proof-of-principle ” for a global understanding of protein dispensability through computational analyses of high-throughput data. 1
Keyphrases
protein dispensability high-throughput data multiple-source high-throughput data integrated analysis gene function computational analysis genome scale genomic sequence data neural network growth rate yeast saccharomyces cerevisia significant correlation correspondence analysis fitness score recent advance duplication rate growth-rate data individual gene phenotype level support vector machine substantial information gene-expression data global understanding protein-protein interaction data evolutionary rate gene-deletion mutant significant dependency gene-expression correlation network protein-protein interaction network
