Network Analysis Tools: from biological networks to clusters and pathways

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Abstract

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein–protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in 1 h.

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Figure 1: Flow chart of the data, tools and results described in this protocol.
Figure 2: Mapping of the clusters obtained with the MCL algorithm on the STRING database data set.
Figure 3: Fuzzy-clusters obtained by combining MCL and the graph-cluster-membership tools.
Figure 4: Most significant associations between MCL clusters versus MIPS complexes.
Figure 5: Result of the fusion between the BioGRID synthetic lethality data set (reference graph) and the yeast–protein interaction data set annotated in the STRING database (query graph).
Figure 6: Result obtained with Pathfinder upon execution of protocol with the study case.

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Acknowledgements

S.B. is the recipient of a PhD grant from the Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture (FRIA). K.F. is supported by the Actions de Recherches Concertées de la Communauté Française de Belgique (ARC grant number 04/09-307). G.L.-M. was funded by a PhD grant from the Fonds Xenophilia [Université Libre de Bruxelles (ULB)] and by a postdoctoral fellowship from the Région Wallonne de Belgique (TransMaze project 415925). The BiGRe laboratory is supported by the BioSapiens Network of Excellence funded under the sixth Framework program of the European Communities (LSHG-CT-2003-503265) and by the Belgian Program on Interuniversity Attraction Poles, initiated by the Belgian Federal Science Policy Office, project P6/25 (BioMaGNet). We acknowledge the students of the Master in Bioinformatics and Modeling (ULB, Belgium) for their useful corrections and suggestions. S.B. and K.F. equally contributed to this article.

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Correspondence to Jacques van Helden.

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Brohée, S., Faust, K., Lima-Mendez, G. et al. Network Analysis Tools: from biological networks to clusters and pathways. Nat Protoc 3, 1616–1629 (2008) doi:10.1038/nprot.2008.100

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