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

2004

Article

ei


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.

Author(s): Weston, J. and Elisseeff, A. and Zhou, D. and Leslie, C. and Noble, WS.
Journal: Proceedings of the National Academy of Science
Volume: 101
Number (issue): 17
Pages: 6559-6563
Year: 2004
Day: 0

Department(s): Empirische Inferenz
Bibtex Type: Article (article)

Digital: 0
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: Web

BibTex

@article{2586,
  title = {Protein ranking: from local to global structure in the protein similarity network},
  author = {Weston, J. and Elisseeff, A. and Zhou, D. and Leslie, C. and Noble, WS.},
  journal = {Proceedings of the National Academy of Science},
  volume = {101},
  number = {17},
  pages = {6559-6563},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  year = {2004}
}