Game Theory applied to gene expression analysis |
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Authors: | Stefano Moretti |
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Institution: | (1) Unit of Molecular Epidemiology, National Cancer Research Institute, L.go R.Benzi 10, 16132 Genoa, Italy |
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Abstract: | This is a summary of the author’s Ph.D. thesis supervised by Fioravante Patrone and Stefano Bonassi and defended on 25 May
2006 at the Università degli Studi di Genova. The thesis in written in English and a copy is available from the author upon
request. This work deals with the discussion and the application of a methodology based on Game Theory for the analysis of
gene expression data. Nowadays, microarray technology is available for taking “pictures” of gene expressions. Within a single
experiment of this sophisticated technology, the level of expression of thousands of genes can be estimated in a sample of
cells under given conditions. Roughly speaking, the starting point is the observation of a “picture” of gene expressions in
a sample of cells under a biological condition of interest, for example a tumor. Then, Game Theory plays a primary role to
quantitatively evaluate the relevance of each gene in regulating or provoking the condition of interest, taking into account
the observed relationships in all subgroups of genes.
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Keywords: | Coalitional game Shapley value Power index Gene expression Microarray |
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