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Pagel, P. ; Strack, N.* ; Oesterheld, M.* ; Stuempflen, V. ; Frishman, D.

Computational prediction of domain interactions.

Methods Mol. Biol. 396, 3-15 (2007)
Zum Artikel PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Conserved domains carry many of the functional features found in the proteins of an organism. This includes not only catalytic activity, substrate binding, and structural features but also molecular adapters, which mediate the physical interactions between proteins or proteins with other molecules. In addition, two conserved domains can be linked not by physical contact but by a common function like forming a binding pocket. Although a wealth of experimental data has been collected and carefully curated for protein-protein interactions, as of today little useful data is available from major databases with respect to relations on the domain level. This lack of data makes computational prediction of domain-domain interactions a very important endeavor. In this chapter, we discuss the available experimental data (iPfam) and describe some important approaches to the problem of identifying interacting and/or functionally linked domain pairs from different kinds of input data. Specifically, we will discuss phylogenetic profiling on the level of conserved protein domains on one hand and inference of domain-interactions from observed or predicted protein-protein interactions datasets on the other. We explore the predictive power of these predictions and point out the importance of deploying as many different methods as possible for the best results.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Herausgeber Bergman, N.H.*
Korrespondenzautor
ISSN (print) / ISBN 1064-3745
e-ISSN 1940-6029
Konferenztitel Comparative Genomics
Zeitschrift Methods in Molecular Biology
Quellenangaben Band: 396, Heft: , Seiten: 3-15 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Berlin [u.a.]
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Bioinformatics and Systems Biology (IBIS)