|HEAD||Dr SCHWIKOWSKI Benno / email@example.com|
|MEMBERS||Dr AITTOKALLIO Tero / Dr BOCHET Pascal / Dr MAZURIE Aurélien / Dr VANDENBOGAERT Mathias / Dr ZHANG Runxuan
The Systems Biology Group was founded in 2004. Its mission is to initiate and execute Systems approaches to biology from a computational side. Its goals lie in two defining areas for Systems Biology: 1) Create technologies to measure biological systems on a large scale. 2) Develop approaches to biological problems that build on integrative analyses of multiple large-scale data sets. The specific aims we currently pursue are 1) To develop methods and tools to more effectively interpret proteomic experiments on mass spectrometers ("Mass spec informatics"), and 2) To develop approaches, methods, and tools for the integration of large-scale data along genomic, temporal, organizational, and evolutionary scales ("Data integration").
As of early 2007, the group is a “dry lab” and consists primarily of Ph.D.s trained in the formal sciences with interdisciplinary project experience. We operate in collaborations with local, national and international laboratories.
BaSysBio: An integrated EU Systems Biology project among 16 different institutions aimed at a high-level understanding carbon metabolism and defined stress responses of B. subtilis. Our group is responsible for a workpackage in which we explore network modularization techniques and create mass spectrometry informatics approaches to integrate information from a large number of experiments.
Cytoscape: A 5-year, NIH-funded collaboration with 5 other organizations in the United States (academia and industry) to create the standard visualization tool for systems biology. Cytoscape is the most commonly used tool for visualization molecular interaction networks and associated data.
CoGenY: Comparative Gene Expression in Yeast. A collaboration with the laboratory of Naama Barkai at the Weizmann Institute, funded by the Pasteur-Weizmann foundation. We explore the evolution of mating function through comparative analysis of gene expression time series in four different yeast interaction networks.
CPAS-IP: Computational Proteomics Analysis System at IP. IP-funded collaboration with the IP mass spec platform and the CPAS group at the Fred Hutchinson Cancer Research Center (Seattle) to implement and improve an open-source computa–tional proteomics data management system. This system will 1) implement of state-of-the-art prote–ome informatics technology at IP, and 2) serve as basis for ongoing and future research in proteomics.
Keywords: Bioinformatics, modeling, proteomics, molecular interaction networks, data integration
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Activity Reports 2006 - Institut Pasteur
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