[email protected]é Libre de Bruxelles, Belgique
Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)http://www.bigre.ulb.ac.be/
Biochemical networks and pathways
Sylvain Brohée & Jacques van Helden(with the help of Gipsi Lima-Mendez)
BioSapiens 9th European School of Bioinformatics
Bioinformatique des Génomes et des Réseaux (BiGRe)Université Libre de Bruxelles
2
Development and application of bioinformatics methods for the analysis of genome function, regulation and evolution.
Regulatory sequences
Pattern discovery algorithms• Olivier Sand (Postdoc)
• Matthieu Defrance (Postdoc)
• Maud Vidick (Master thesis) Evolution of cis-acting elements in Bacteria
• Rekin’s Janky (PhD student) Regulation of development in Drosophila
• Jean Valéry Turatsinze (PhD student) Hox regulation in Vertebrates
• Morgane Thomas-Chollier (PhD student) Regulation of phages and prophages
• Rossy Gabin Nkoubouala (Master student) Work flows on transcriptional regulation
• Eric Vervisch (Research fellow) Molecular networks
Analysis of regulatory networks• Rekin’s Janky (PhD student),Sylvain Brohée (PhD student)
Interactions between membrane-associated proteins• Sylvain Brohée (PhD student)
Inference of metabolic pathways• Karoline Faust (PhD student)
Signal transduction pathways• Olivier Sand (Postdoc)
Mobile genetic elements in prokaryotes
• Raphaël Leplae (Postdoc)
• Gipsi Lima (PhD student)
• Ariane Toussaint (Professor) Modelling of dynamical systems
• Didier Gonze (Premier assistant)
Gipsi LimaPostdoc
Ariane ToussaintProfessor
Raphaël LeplaePostdoc
Jean Valéry TuratsinzePhD student
Rekin’s JankyEx-PhD student
Morgane Thomas-Chollier
Postdoc
Olivier SandPostdoc
Jacques van HeldenChargé de cours
Matthieu DefrancePostdoc
Sylvain BrohéePostdoc
Karoline FaustPhD student
Didier GonzePremier assistant
Eric VervischEx-Research fellow
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Myriam LoubriatSecretary
Jean-Valéry TuratsinzePhD student
Graph-based analysis of biochemical networks
9th BioSapiens European School of BioinformaticsUniversité Libre de Bruxelles, Jan 29, 2009
Graph-based analysis of biochemical networksTeachers: Sylvain Brohée & Jacques van HeldenFrom To Nb Topics Teacher Type
9:00 9:05 0 Introduction Jacques van Helden
9:05 9:35 1 Biochemical networks : basic concepts and definitions Jacques van Helden
Theory
9:35 10:05 2 Software tools for network visualization Sylvain Brohée Tutorial
10:05 10:15 3 NeAT, a generic toolbox for the analysis of biochemical networks
Sylvain Brohée Quick tour
10:15 10:45 4 Topological properties Jacques van Helden
Theory
10:45 11:00 Coffee break11:00 11:15 5 Analyzing graph topology with NeAT Sylvain Brohée Practicals11:15 11:35 6 Path finding Jacques van
HeldenTheory
11:35 12:05 7 Path finding with NeAT Jacques van Helden
Practicals
11:35 11:50 8 Graph comparisons Sylvain Brohée Theory11:50 12:05 9 Network randomization Sylvain Brohée Theory12:05 12:50 10 Random graph and graph comparision with NeAT Sylvain Brohée Practicals12:45 14:00 Lunch14:00 14:30 11 Extracting modules from interaction networks Sylvain Brohée Theory14:30 15:30 12 Analyzing network modules with NeAT Sylvain Brohée Practicals15:40 16:00 Coffee break
Links and references
Network Analysis Tools (NeAT) http://rsat.ulb.ac.be/neat/
Publications1. van Helden, J., Naim, A., Mancuso, R., Eldridge, M., Wernisch, L., Gilbert, D. & Wodak, S. (2000).
Representing and analyzing molecular and cellular function in the computer. Biological Chemistry 381, 921-935.
2. van Helden, J., Naim, A., Lemer, C., Mancuso, R., Eldridge, M. & Wodak, S. (2001). From molecular activities and processes to biological function. Briefings in Bioinformatics 2(1), 81-93.
3. van Helden, J., Gilbert, D., Wernisch, L., Schroeder, M. & Wodak, S. (2001). Applications of regulatory sequence analysis and metabolic network analysis to the interpretation of gene expression data. Lecture Notes in Computer Sciences 2066, 155-172.
4. van Helden, J., Wernisch, L., Gilbert, D. & Wodak, S. (2002). Graph-based analysis of metabolic networks. In Bioinformatics and Genome Analysis (Mewes, H.-W., Weiss, B. & Seidel, H., eds.), Vol. 38. Springer-Verlag, Berlin Heidelberg.
5. Deville, Y., D. Gilbert, J. van Helden, and S.J. Wodak (2003). An overview of data models for the analysis of biochemical pathways. Brief Bioinform 4: 246-259.
6. Croes, D., F. Couche, S.J. Wodak, and J. van Helden (2005). Metabolic PathFinding: inferring relevant pathways in biochemical networks. Nucleic Acids Res 33: W326-330.
7. Croes, D., F. Couche, S.J. Wodak, and J. van Helden (2006). Inferring meaningful pathways in weighted metabolic networks. J Mol Biol 356: 222-236.
8. Brohee, S. & van Helden, J. (2006). Evaluation of clustering algorithms for protein-protein interaction networks. BMC Bioinformatics 7, 488.
9. Brohee, S., Faust, K., Lima-Mendez, G., Vanderstocken, G. and van Helden, J. (2008). Network Analysis Tools: from biological networks to clusters and pathways. Nat Protoc 3, 1616-29.
10. Brohee, S., Faust, K., Lima-Mendez, G., Sand, O., Janky, R., Vanderstocken, G., Deville, Y. and van Helden, J. (2008). NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways. Nucleic Acids Res.