Bioinformatic analysis of variations in the human genome and of their relationship with disease


Abstract : During the last few years, high-throughput sequencing technologies have become much less expensive, and have produced massive amounts of data. The analysis and the exploitation of these data is one of the major current challenges in genomics and bioinformatics. In particular, millions of Single Nucleotide Polymorphisms (SNP) have been identified by collaborative projects. Each SNP may affect the expression or function of one or several genes, and have as a consequence an impact on the functioning of the living organism. Non-synonymous SNPs that occur within coding regions of the DNA are of particular interest since they lead to differences in the sequences of the expressed proteins. The annotation of these variations and of their impact on human health is an important step towards a better understanding of the genetic background of hereditary diseases, and towards the development of personalized therapeutic approaches for complex diseases. The project consists of developing an automatic approach for the analysis of non-synonymous coding SNPs data in view of predicting their possible relationship with disease. The approach will focus more specifically on the exploitation of structural information about the variant proteins. These models will be subjected to various structural analysis tools, in view of predicting the effects of SNPs and their relationship with the development of diseases.
Promoteur/Supervisor : Prof. Rooman Marianne
Email : mrooman@ulb.ac.be
Site Web/Web site :
Centre de recherche/Research center : 3BIO - BioModeling, BioInformatics & BioProcesses
Faculté/Faculty : Faculté des Sciences appliquées - école polytechnique/Brussels School of Engineering (Faculty of Applied Sciences)
Ecole doctorale/Graduate Colleges : Sciences agronomiques et ingénierie biolo/Agronomy and Bioengineering
Ecole doctorale thématique/Graduate School (French Only): Structure et fonction des macromolécules biologiques, bioinformatique et modélisation (SFMBBM)



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