GRAPHLET ALIGNMENT IN PROTEIN INTERACTION NETWORKS Conference Paper

abstract

• With the increased availability of genome-scale data, it becomes possible to study functional relationships of genes across multiple biological networks. While most previous approaches for studying conservation of patterns in networks are through the application of network alignment algorithms or the identification of network motifs, we show that it is possible to exhaustively enumerate all graphlet alignments, which consist of subgraphs from each network that share a common topology and contain homologous proteins at the same position in the topology. We show that our algorithm is able to cover significantly more proteins than previous network alignment algorithms while achieving comparable specificity and higher sensitivity with respect to functional enrichment. 2010 IEEE.

name of conference

• 2010 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)

authors

• Sze, Sing-Hoi

published proceedings

• 2010 IEEE INTERNATIONAL WORKSHOP ON GENOMIC SIGNAL PROCESSING AND STATISTICS (GENSIPS)

author list (cited authors)

• Hsieh, M., & Sze, S.

citation count

• 0

complete list of authors

• Hsieh, Mu-Fen||Sze, Sing-Hoi

publication date

• January 2010

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics  Journal

keywords

• Network Alignment
• Network Motif
• Protein Interaction Network

Digital Object Identifier (DOI)

• 10.1109/gensips.2010.5719676

International Standard Book Number (ISBN) 13

• 9781612847924

start page

• 1

end page

• 4

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Fgensips.2010.5719676