Jacques.van.Helden@ulb.ac.beUniversité 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.