Network Analysis Tools (NeAT) - Credits
The Network Analysis Tools integrate a set of programs implemented at the Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe), plus a few programs developed by third parties (with the authorization of their authors).
Developers
The programs for handling graphs and clusters (conversion, comparisons, display) were mainly developed by Sylvain Brohée and Jacques van Helden.
The backtrack algorithm for metabolic path finding was principally developed by Fabian Couche and Didier Croes and is available here. The path finding web service implemented by Karoline Faust for NeAT relies on REA (Jimenez & Marzal, 1999) and can be applied to any network. Both path finding tools were developed under the supervision of Jacques van Helden.
The MCL algorithm for graph-based clustering was developed by Stijn van Dongen (Sanger Institute, UK). We are thankful to Stijn for making the MCL code publicly available, for allowing us to integrate it in our Web server, and for his extensive feed-back on the NeAT web interface.
The RNSC algorithm for graph-based clustering was developed by Andrew King (McGill Institute, Canada). We are thankful to Andrew for making the RNSC code publicly available, for allowing us to integrate it in our Web server and our web services.
The respective contributions are indicated in more detail in the manual pages of each tool.
Acknowledgements
We acknowledge the following colleagues for their constructive comments and suggestions about the NeAT interface:
- Stijn Van Dongen (Sanger Institute, UK)
- Bruno Contreras Moreira (Univ. Saragosa, Spain)
- Alexandre Irrthum (ULg, Belgium) and his students
- Cei Abreu (Sanger Institue, UK)
- Philippe Gautier (MRC Edimburg, UK)
- Nicolas Simonis (Harvard medical school, Boston, USA)
- Shuye Pu (Hospital for Sick Children, Toronto, Canada)
Sample data sets
The sample data sets have been taken from:
Funding
- Sylvain Brohée is the recipient of a PhD grant from the Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture (FRIA).
- The PhD grant of Karoline Faust is supported by The Actions de Recherches Concertées de la Communauté Française de Belgique (ARC grant number 04/09-307).
Libraries
- display-graph uses the PostScript-Simple an GD perl libraries.
- convert-graph and display-graph uses the Fruchterman and Reingold layout algorithm available in the boost graph library.
- Pathfinder calls REA (Jimenez & Marzal, 1999) as k shortest paths algorithm (modified by Jean-Noël Monette and Pierre Schaus) and uses a graph library developed by the former aMAZE team.
- Metabolic pathfinder makes use of Hibernate and a database implemented in postgres storing KEGG data in order to label compounds and reactions. In addition, it makes use of graphviz to display graphs.
- KEGG network provider uses KEGG PATHWAY data.