Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable

BACKGROUND: By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Naïve Bayes and other machine learning algorithms we are able to distinguish between two classes of protein sequences: those folding to highly-designable conformations, or th...

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Bibliographic Details
Main Authors: Peto, Myron, Kloczkowski, Andrzej, Honavar, Vasant, Jernigan, Robert L
Format: Artigo
Language:Inglês
Published: BioMed Central 2008
Subjects:
Research Article
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC2655094/
https://ncbi.nlm.nih.gov/pubmed/19014713
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-9-487
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