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Thesis

French

ID: <

10670/1.zdbmuc

>

Where these data come from
Regulatory networks analysis with graph coloring approaches applied to multiple myeloma

Abstract

During the last two decades, the huge increase of biological data production capacity and biological interactions knowledge leads to the development of many approaches integrating data and global knowledge. Our main aim was to propose new methods to characterize and compare genes expression profiles from cancer cells and normal plasma cells. For this purpose, we proposed 2 methods based on graph coloring. The first, which is able to infer the state of proteins and transcription factors from a genes expression profile, allowed us to identify transcription factor activity involved in tumors. The second method is able to identify independent subgraph (the components) based on perfect colorations. With this approach, we evaluated the similarity between genes expression profiles and "perfect states" of the components and were able to identify subgraphs specifically perturbated in cancer cells associated with oncogenic process.

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