ArticleBMC bioinformatics2008
A genetic approach for building different alphabets for peptide and protein classification.
Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 37 citations in OpenAlex.
- Amino Acid Reduction Can Help to Improve the Identification of Antimicrobial Peptides and Their Functional Activities.Frontiers in genetics · 2021Article
- PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein-Protein Interactions from Protein Sequences.International journal of molecular sciences · 2017Article
- Prediction of ketoacyl synthase family using reduced amino acid alphabets.Journal of industrial microbiology & biotechnology · 2012Article
- Improved Bevirimat resistance prediction by combination of structural and sequence-based classifiers.BioData mining · 2011Article
- Conotoxin protein classification using free scores of words and support vector machines.BMC bioinformatics · 2011Article
- Enzyme classification with peptide programs: a comparative study.BMC bioinformatics · 2009Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn 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.
resultsThe 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.
conclusionThe validity of the novel strategy for creating reduced alphabets is demonstrated by the performance improvement obtained by the proposed approach with respect to other reduced alphabets-based methods in the tested problems.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.