Serge Moulin " Providing data analysis to solve specific problems in bioinformatics"

Work thesis of Serge Moulin : "Providing data analysis techniques to solve specific problems in bioinformatics"

Abstract : Today, the amount of sequenced genetic data is increasing exponentially under the impetus of increasingly powerful sequencing tools, such as high throughput sequencing tools in particular. In addition, these data are increasingly accessible through online databases. This greater availability of data opens up new topics of study that require statisticians and bioinformaticians to develop appropriate tools. Moreover, constant progress in statistics, in areas such as clustering, dimension reduction, or regressions among others, need to be regularly adapted to the context of bioinformatics. The objective of this thesis is the application of advanced statistical techniques to bioinformatics issues. In this manuscript, we present the results of our work concerning the clustering of genetic sequences via Laplacian eigenmaps and Gaussian mixing model, the study of the propagation of transposable elements in the genome via a branching process, the analysis of metagenomic data in ecology via ROC curves or ordered polytomic regression penalized by the norm l1.

Jury of thesis : 

Christophe GUYEUX directeur de thèse

Stephane CHRETIEN co-directeur de thèse

Julien JACQUES rapporteur

Arnaud LE ROUZIC rapporteur

Location : Amphithéâtre 4 - IUT Belfort-Montbéliard - 19, Avenue du Maréchal Juin 90016 BELFORT