Functional classification of proteins for the prediction of cellular function from a protein-protein interaction network

Genome Biology

Volume 5
Issue 1

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Brun C
Chevenet F
Martin D
Wojcik J
Guénoche A
Jacq B

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Chevenet F
Martin D
Wojcik J
Guénoche A
Jacq B
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Functional classification of proteins for the prediction of cellular function from a protein-protein interaction network

Christine Brun¹, François Chevenet²^*, David Martin¹^*, Jérôme Wojcik³, Alain Guénoche⁴ and Bernard Jacq¹

¹Laboratoire de Génétique et Physiologie du Développement, CNRS UMR6545, Parc Scientifique et Technologique de Luminy, Case 907, 13288 Marseille Cedex 9, France

²Centre d'Etude sur le Polymorphisme des Micro-organismes, CNRS/IRD UMR 9926, 911 avenue Agropolis, BP 6450, 34394 Montpellier Cedex 5, France

³Hybrigenics SA, 3/5 impasse Reille, 75014 Paris, France

⁴Institut de Mathématiques de Luminy, CNRS UPR9016, Parc Scientifique et Technologique de Luminy, Case 907, 13288 Marseille Cedex 9, France

author email corresponding author email* Contributed equally

Genome Biology 2003, 5:R6


Published:	15 December 2003

Subject areas: Bioinformatics, Methods, Genome studies

Additional files

Additional data file 1:

Composition of the 63 PRODISTIN classes. Numbers in column ''Cellular Role' Annotation' indicate founder proteins for each class (see Fig. 3 legend). When two 'Cellular Roles' are assigned to a same class, 1 and 2 indicate proteins annotated with the first one and/or the second class respectively. A question mark (?) marks proteins of unknown function. The class robustness index is indicated for each class

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Additional data file 2:

Details of the functional predictions and comparisons with predictions obtained by other means

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