Isofunctional Protein Subfamily Detection Using Data Integration and Spectral Clustering

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Elisa {Boari de Lima} and Wagner {Meira Jr.} and 
                 Raquel {Cardoso de Melo-Minardi}",
  journal =      "PLoS Computational Biology",
  title =        "Isofunctional Protein Subfamily Detection Using Data
                 Integration and Spectral Clustering",
  year =         "2016",
  volume =       "12",
  number =       "6",
  pages =        "1005001",
  month =        "27 " # jun,
  keywords =     "genetic algorithms, genetic programming, Serine
                 proteases, Sequence alignment, Protein domains,
                 Dehydration (medicine), Protein kinases, Protein
                 structure comparison, Adenylyl cyclase, Protein
  publisher =    "Public Library of Science",
  DOI =          "doi:10.1371/journal.pcbi.1005001",
  size =         "32 pages",
  abstract =     "The knowledge of protein functions is central for
                 understanding life at a molecular level and has huge
                 biochemical and pharmaceutical implications. However,
                 despite best research efforts, a substantial and
                 ever-increasing number of proteins predicted by genome
                 sequencing projects still lack functional annotations.
                 Computational methods are required to determine protein
                 functions quickly and reliably since experimental
                 investigation is difficult and costly. Considering
                 literature shows combining various types of information
                 is crucial for functionally annotating proteins, such
                 methods must be able to integrate data from different
                 sources which may be scattered, non-standardized,
                 incomplete, and noisy. Many protein families are
                 composed of proteins with different folds and
                 functions. In such cases, the division into subtypes
                 which share specific functions uncommon to the family
                 as a whole may lead to important information about the
                 function and structure of a related protein of unknown
                 function, as well as about the functional
                 diversification acquired by the family during
                 evolution. This work's purpose is to automatically
                 detect isofunctional subfamilies in a protein family of
                 unknown function, as well as identify residues
                 responsible for differentiation. We integrate data and
                 then provide it to a clustering algorithm, which
                 creates clusters of similar proteins we found
                 correspond to same-specificity subfamilies",
  notes =        "International Society for Computational Biology",

Genetic Programming entries for Elisa Boari de Lima Wagner Meira Raquel Cardoso de Melo-Minardi