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RECOMB Workshop on Comparative Genomics

RCG 2006: Comparative Genomics pp 11–23Cite as

Domain Architecture in Homolog Identification

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4205))

Abstract

Homology identification is the first step for many genomic studies. Current methods, based on sequence comparison, can result in a substantial number of mis-assignments due to the alignment of homologous domains in otherwise unrelated sequences. Here we propose methods to detect homologs through explicit comparison of domain architecture. We developed several schemes for scoring the similarity of a pair of protein sequences by exploiting an analogy between comparing proteins using their domain content and comparing documents based on their word content. We evaluate the proposed methods using a benchmark of fifteen sequence families of known evolutionary history. The results of these studies demonstrate the effectiveness of comparing domain architectures using these similarity measures. We also demonstrate the importance of both weighting critical domains and of compensating for proteins with large numbers of domains.

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Author information

Authors and Affiliations

  1. Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    N. Song, R. D. Sedgewick & D. Durand

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  1. N. Song
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  2. R. D. Sedgewick
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  3. D. Durand
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Editor information

Editors and Affiliations

  1. Genome Institute of Singapore, 138672, Republic of Singapore

    Guillaume Bourque

  2. DIRO, Université de Montréal, H3C 3J7, Canada

    Nadia El-Mabrouk

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© 2006 Springer-Verlag Berlin Heidelberg

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Song, N., Sedgewick, R.D., Durand, D. (2006). Domain Architecture in Homolog Identification. In: Bourque, G., El-Mabrouk, N. (eds) Comparative Genomics. RCG 2006. Lecture Notes in Computer Science(), vol 4205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11864127_2

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  • DOI: https://doi.org/10.1007/11864127_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44529-6

  • Online ISBN: 978-3-540-44530-2

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