Section: Application Domains

Analysis of genomic data

Since many years select collaborates with Marie-Laure Martin-Magniette (URGV) for the analysis of genomic data. An important theme of this collaboration is using statistically sound model-based clustering methods to discover groups of co-expressed genes from microarray and high-throughput sequencing data. In particular, identifying biological entities that share similar profiles across several treatment conditions, such as co-expressed genes, may help identify groups of genes that are involved in the same biological processes. Yann Vasseur started a thesis cosupervised by Gilles Celeux and Marie-Laure Martin-Magniette on this topic which is also an interesting investigation domain for the latent block model developed by select . On an other hand, select is involved in ANR “jeunes chercheurs” MixStatSeq directed by Cathy Maugis (INSA Toulouse) wich is concerned with Statistical analysis and clustering of RNASeq genomics data.