TY - JOUR
T1 - Network analysis tools
T2 - From biological networks to clusters and pathways
AU - Brohée, Sylvain
AU - Faust, Karoline
AU - Lima-Mendez, Gipsi
AU - Vanderstocken, Gilles
AU - van Helden, Jacques
N1 - Funding Information:
ACKNOWLEDGMENTS 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 Franc¸aise 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.
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=52749089913&partnerID=8YFLogxK
U2 - 10.1038/nprot.2008.100
DO - 10.1038/nprot.2008.100
M3 - Article
C2 - 18802442
AN - SCOPUS:52749089913
SN - 1754-2189
VL - 3
SP - 1616
EP - 1629
JO - Nature Protocols
JF - Nature Protocols
IS - 10
ER -