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Cube-DB: detection of functional divergence in human protein families.


ABSTRACT: Cube-DB is a database of pre-evaluated results for detection of functional divergence in human/vertebrate protein families. The analysis is organized around the nomenclature associated with the human proteins, but based on all currently available vertebrate genomes. Using full genomes enables us, through a mutual-best-hit strategy, to construct comparable taxonomical samples for all paralogues under consideration. Functional specialization is scored on the residue level according to two models of behavior after divergence: heterotachy and homotachy. In the first case, the positions on the protein sequence are scored highly if they are conserved in the reference group of orthologs, and overlap poorly with the residue type choice in the paralogs groups (such positions will also be termed functional determinants). The second model additionally requires conservation within each group of paralogs (functional discriminants). The scoring functions are phylogeny independent, but sensitive to the residue type similarity. The results are presented as a table of per-residue scores, and mapped onto related structure (when available) via browser-embedded visualization tool. They can also be downloaded as a spreadsheet table, and sessions for two additional molecular visualization tools. The database interface is available at http://epsf.bmad.bii.a-star.edu.sg/cube/db/html/home.html.

SUBMITTER: Zhang ZH 

PROVIDER: S-EPMC3245124 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature

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Cube-DB: detection of functional divergence in human protein families.

Zhang Zong Hong ZH   Bharatham Kavitha K   Chee Sharon M Q SM   Mihalek Ivana I  

Nucleic acids research 20111201 Database issue


Cube-DB is a database of pre-evaluated results for detection of functional divergence in human/vertebrate protein families. The analysis is organized around the nomenclature associated with the human proteins, but based on all currently available vertebrate genomes. Using full genomes enables us, through a mutual-best-hit strategy, to construct comparable taxonomical samples for all paralogues under consideration. Functional specialization is scored on the residue level according to two models o  ...[more]

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