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Comparative Study
. 2004 Oct 25:5:158.
doi: 10.1186/1471-2105-5-158.

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

Yin Liu  1 , Hongyu Zhao
Affiliations
Comparative Study

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

Yin Liu et al. BMC Bioinformatics. .

Abstract

Background: 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. However, despite their importance, research on signaling pathways reconstruction utilizing large-scale genomics and proteomics information has been limited.

Results: We 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.

Conclusions: As 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.

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Figures

Figure 1
Figure 1
MAPK signaling pathways in Saccharomyces cerevisiae. Membrane receptors are marked in blue, and transcription factors are marked in red. The figure is adapted from KEGG pathway database [12], and the scaffold proteins and proteins on the pathway branches are omitted for simplicity.
Figure 2
Figure 2
Distribution of the scores for permuted pheromone response pathways. (a) Scores based on protein-protein interaction data, (b) Scores based on microarray gene expression data, (c) the integrated scores based on both protein-protein interaction data and gene expression data.
See this image and copyright information in PMC

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