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BMCBI
2008

A genetic approach for building different alphabets for peptide and protein classification

8 years 8 months ago
A genetic approach for building different alphabets for peptide and protein classification
Background: In this paper, it is proposed an optimization approach for producing reduced alphabets for peptide classification, using a Genetic Algorithm. The classification task is performed by a multi-classifier system where each classifier (Linear or Radial Basis function Support Vector Machines) is trained using features extracted by different reduced alphabets. Each alphabet is constructed by a Genetic Algorithm whose objective function is the maximization of the area under the ROC-curve obtained in several classification problems. Results: The new approach has been tested in three peptide classification problems: HIV-protease, recognition of T-cell epitopes and prediction of peptides that bind human leukocyte antigens. The tests demonstrate that the idea of training a pool classifiers by reduced alphabets, created using a Genetic Algorithm, allows an improvement over other state-of-the-art feature extraction methods. Conclusion: The validity of the novel strategy for creating red...
Loris Nanni, Alessandra Lumini
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2008
Where BMCBI
Authors Loris Nanni, Alessandra Lumini
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