Alignment using genetic programming with causal trees for identification of protein functions

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  author =       "Chun-Min Hung and Yueh-Min Huang and Ming-Shi Chang",
  title =        "Alignment using genetic programming with causal trees
                 for identification of protein functions",
  journal =      "Nonlinear Analysis",
  year =         "2006",
  volume =       "65",
  number =       "5",
  pages =        "1070--1093",
  month =        "1 " # sep,
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1016/",
  abstract =     "A hybrid evolutionary model is used to propose a
                 hierarchical homology of protein sequences to identify
                 protein functions systematically. The proposed model
                 offers considerable potentials, considering the
                 inconsistency of existing methods for predicting novel
                 proteins. Because some novel proteins might align
                 without meaningful conserved domains, maximising the
                 score of sequence alignment is not the best criterion
                 for predicting protein functions. This work presents a
                 decision model that can minimise the cost of making a
                 decision for predicting protein functions using the
                 hierarchical homologies. Particularly, the model has
                 three characteristics: (i) it is a hybrid evolutionary
                 model with multiple fitness functions that uses genetic
                 programming to predict protein functions on a distantly
                 related protein family, (ii) it incorporates modified
                 robust point matching to accurately compare all feature
                 points using the moment invariant and thin-plate spline
                 theorems, and (iii) the hierarchical homologies holding
                 up a novel protein sequence in the form of a causal
                 tree can effectively demonstrate the relationship
                 between proteins. This work describes the comparisons
                 of nucleocapsid proteins from the putative polyprotein
                 SARS virus and other coronaviruses in other hosts using
                 the model.",
  notes =        "Hybrid Systems and Applications",

Genetic Programming entries for Chun-Min Hung Yueh-Min Huang Ming-Shi Chang