AlignNemo: a local network alignment method to integrate homology and topology.

Détails

ID Serval
serval:BIB_EC2086440E33
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
AlignNemo: a local network alignment method to integrate homology and topology.
Périodique
PloS one
Auteur(s)
Ciriello G., Mina M., Guzzi P.H., Cannataro M., Guerra C.
ISSN
1932-6203 (Electronic)
ISSN-L
1932-6203
Statut éditorial
Publié
Date de publication
2012
Peer-reviewed
Oui
Volume
7
Numéro
6
Pages
e38107
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Résumé
Local network alignment is an important component of the analysis of protein-protein interaction networks that may lead to the identification of evolutionary related complexes. We present AlignNemo, a new algorithm that, given the networks of two organisms, uncovers subnetworks of proteins that relate in biological function and topology of interactions. The discovered conserved subnetworks have a general topology and need not to correspond to specific interaction patterns, so that they more closely fit the models of functional complexes proposed in the literature. The algorithm is able to handle sparse interaction data with an expansion process that at each step explores the local topology of the networks beyond the proteins directly interacting with the current solution. To assess the performance of AlignNemo, we ran a series of benchmarks using statistical measures as well as biological knowledge. Based on reference datasets of protein complexes, AlignNemo shows better performance than other methods in terms of both precision and recall. We show our solutions to be biologically sound using the concept of semantic similarity applied to Gene Ontology vocabularies. The binaries of AlignNemo and supplementary details about the algorithms and the experiments are available at: sourceforge.net/p/alignnemo.
Mots-clé
Conserved Sequence, Proteins/chemistry, Sequence Alignment/methods, Sequence Homology, Amino Acid
Pubmed
Web of science
Open Access
Oui
Création de la notice
06/07/2018 11:02
Dernière modification de la notice
20/08/2019 16:14
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