| Summary: | 碩士 === 亞洲大學 === 生物資訊學系碩士班 === 96 === Signal transduction plays an important role in the control of most fundamental cellular processes by which cells convert an external signal into a response.
In this study we present a computational approach that integrates different types of information to predict the order of the signal transduction pathway components assuming all the pathway components 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 dataset, either protein interactions or gene transcript abundance measurements, the integrated approach leads to better identification of the order of the pathway components.
Our method can lead to a good prediction for the well-known yeast MAPK signaling pathways. Therefore, we conjecture that this approach may be applicable to many other pathways including less well understood ones. In addition,we use our approach to predict the combination order of protein complexes with three or four subunits.And we set up a web interface (http://210.70.83.81/pop/) to show the results.
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