1st International ICST Workshop on Game Theory for Networks

Research Article

Minimum cost spanning tree situations and gene expression data analysis

  • @INPROCEEDINGS{10.1145/1190195.1190203,
        author={Stefano  Moretti},
        title={Minimum cost spanning tree situations and gene expression data analysis},
        proceedings={1st International ICST Workshop on Game Theory for Networks},
        publisher={ACM},
        proceedings_a={GAMENETS},
        year={2012},
        month={4},
        keywords={minimum costs spanning tree situation cooperative game theory gene expression analysis microarray},
        doi={10.1145/1190195.1190203}
    }
    
  • Stefano Moretti
    Year: 2012
    Minimum cost spanning tree situations and gene expression data analysis
    GAMENETS
    ACM
    DOI: 10.1145/1190195.1190203
Stefano Moretti1,*
  • 1: Unit of Molecular Epidemiology, National Cancer Research Institute (IST), Largo R. Benzi 10, 16132, Genoa, Italy. Telephone number:+39-(0)10-5600500
*Contact email: stefano.moretti@istge.it

Abstract

In [16] a methodology based on Game Theory for the analysis of gene expression data is studied. 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. In this paper, an alternative model based on minimum cost spanning tree representation of gene expression data has been introduced. One of the main characteristics of this model is the possibility to avoid the dichotomization technique required for microarray games introduced in [17].