A computational approach for ordering signal transduction pathway components from genomics and proteomics Data

Yin Liu,Hongyu Zhao

doi:10.1186/1471-2105-5-158

Abstract

BackgroundSignal transduction is one of the most important biological processes by which cells convert an external signal into a response. Novel computational approaches to mapping proteins onto signaling pathways are needed to fully take advantage of the rapid accumulation of genomic and proteomics information. However, despite their importance, research on signaling pathways reconstruction utilizing large-scale genomics and proteomics information has been limited.ResultsWe have developed an approach for predicting the order of signaling pathway components, assuming all the components on the pathways are known. Our method is built on a score function that integrates protein-protein interaction data and microarray gene expression data. Compared to the individual datasets, either protein interactions or gene transcript abundance measurements, the integrated approach leads to better identification of the order of the pathway components.ConclusionsAs demonstrated in our study on the yeast MAPK signaling pathways, the integration analysis of high-throughput genomics and proteomics data can be a powerful means to infer the order of pathway components, enabling the transformation from molecular data into knowledge of cellular mechanisms.

Highlights

Signal transduction is one of the most important biological processes by which cells convert an external signal into a response
As protein-protein interaction plays an important role in achieving the signal transduction process, useful prediction of the order of the pathway components will require knowledge of the interacting partners of these pathway components
We utilize the Database of Interacting Proteins (DIP) that is based on curated collection of all functional linkages of proteins obtained by experimental methods, including yeast two-hybrid experiments, immunoprecipitation, and affinity purification [9]

Summary

Introduction

Signal transduction is one of the most important biological processes by which cells convert an external signal into a response. Novel computational approaches to mapping proteins onto signaling pathways are needed to fully take advantage of the rapid accumulation of genomic and proteomics information Despite their importance, research on signaling pathways reconstruction utilizing large-scale genomics and proteomics information has been limited. Signal transduction is the primary means by which eukaryotic cells respond to external signals from their environment and coordinate complex cellular changes. It plays an important role in the control of most fundamental cellular processes including cell proliferation, metabolism, differentiation, and survival [1]. With the accumulation of genome sequence information, large-scale genomic and proteomic techniques have offered insights into the components of signal transduction pathways and the molecular and cellular responses to cell signaling. Microarray experiments can simultaneously measure the transcript abundance of thousands of genes (page number not for citation purposes)

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