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  Protein ranking: from local to global structure in the protein similarity network

Weston, J., Elisseeff, A., Zhou, D., Leslie, C., & Noble, W. (2004). Protein ranking: from local to global structure in the protein similarity network. Proceedings of the National Academy of Sciences of the United States of America, 101(17), 6559-6563. doi:10.1073/pnas.0308067101.

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Weston, J1, 2, Author           
Elisseeff, A1, 2, Author           
Zhou, D1, 2, Author           
Leslie, C, Author
Noble, WS, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Biologists regularly search databases of DNA or protein sequences for evolutionary or functional relationships to a given query sequence. We describe a ranking algorithm that exploits the entire network structure of similarity relationships among proteins in a sequence database by performing a diffusion operation on a pre-computed, weighted network. The resulting ranking algorithm, evaluated using a human-curated database of protein structures, is efficient and provides significantly better rankings than a local network search algorithm such as PSI-BLAST.

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 Dates: 2004
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1073/pnas.0308067101
BibTex Citekey: 2586
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Title: Proceedings of the National Academy of Sciences of the United States of America
  Other : Proc. Acad. Sci. USA
  Other : Proc. Acad. Sci. U.S.A.
  Other : Proceedings of the National Academy of Sciences of the USA
  Abbreviation : PNAS
Source Genre: Journal
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Publ. Info: Washington, D.C. : National Academy of Sciences
Pages: - Volume / Issue: 101 (17) Sequence Number: - Start / End Page: 6559 - 6563 Identifier: ISSN: 0027-8424
CoNE: https://pure.mpg.de/cone/journals/resource/954925427230