Computationalmethods for the identification of transcriptional regulationmodules

AUTOR(ES)

Paulo Gustavo Soares da Fonseca

DATA DE PUBLICAÇÃO

2008

RESUMO

Recent studies have demonstrated that biological networks display non-random characteristics, among which we highlight the modular architecture. In our thesis, we are interested in the modular organisation of transcriptional regulation networks (TRN), which model the interactions between genes and proteins that control their expression at the transcriptional level. Understanding the mechanisms of transcriptional regulation is crucial to explaining the morphological and functional diversity of cells. We propose to address the problem of identifying transcriptional regulation modules, i.e. groups of co-regulated genes and their regulators, with emphasis on the computational aspect. One important distinction of our work is that we also interest ourselves to the evolutionary aspect of the transcription modules. From the biological point of view, the proposed approach is supported by three main premises: (i) co-regulated genes are bound by common regulatory proteins (transcription factorsâTFs) and so they must present commonsequence patterns (motifs) in their regulatory regions, which correspond to the binding sites of those TFs, (ii) co-regulated genes respond coordinatedly to certain environmental or growth conditions, and so they must be co-expressed under those conditions, and (iii) since transcriptional modules are suposedly responsible for important biological functions, they are more subject to selective pressure and therefore they must be evolutionary conserved. We thus define the concept of a transcriptional regulation metamodules (TRMMs) as groups of genes sharing regulatory motifs and displaying coherent context-specific expression behaviour consistently across species and propose probabilistic models to describe the modular behaviour in terms of the sharing of regulatory elements (motifs), of the co-expression, and of the evolutionary conservation of functional associations between genes based on diverse data such as genomic sequence, gene expression, and phylogenetic data

ASSUNTO(S)

metamÃdulos regulatÃrios transcricionais co-expression analysis motif sharing cÃlculo de p-values biclustering markov models biclustering p-value computation transcriptional regulation metamodules probabilistic models phylogenetic algorithms compartilhamento de motifs pattern recognition modelos de markov transcriptional modules evolutionary models reconhecimento de padrÃes ciencia da computacao anÃlise de co-expressÃo modelos evolutivos de mÃdulos transcricionais algoritmos filogenÃticos modelos probabilÃsticos

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