Computer Science, Mathematics and Physics in Molecular Biology (ACI IMPBIO) action 2004-2007


Integration of gene expression data and gene regulatory networks for the study of cancers

Additional material related to submitted paper Classification of Microarray Data with Gene Networks


The main goal of this project is to develop new methods in order to study various types of tumors by integrating expression and genome microarrays and prior knowledge of various regulatory networks known to be altered in cancer. The analysis is expected to provide new understandings of the molecular biology of tumorigenesis and tumoral progression, as well as new tools to classify tumors. Specifically, our goal is to detect new regulation pathways involved in several types of cancer.

Our approach will be built on the innovative work initiated by Jean-Philippe Vert at the Kyoto University (Vert and Kanehisa, 2003, 2003b ; Yamanishi et al, 2003, 2004), which is based on definite positive kernel theory (Berg et al., 1984)  and Hilbertian statistical learning (Vapnik, 1998 ; Schölkopf and Smola, 2002). This method will be extended to integrate new types of data (the genome microarray data which informs us on the tumoral genome structure, phenotypic variables); and to take into account the peculiarities of regulation networks with respect to metabolic pathways (for which the first tools were designed).

François Radvanyi (UMR144, CNRS/Institut Curie), Marie Dutreix (UMR 2027, CNRS/Institut Curie) and Olivier Delattre (UMR 509, INSERM/Institut Curie) will contribute to the project as expert biologists and will be involved in experimental validation.

Meeting schedule

This project ACI-IMPBIO-2004-47 is supported by the Ministry of Research and New Technologies