Linear Support Vector Machines for HIV-1 Protease Site Detection

Gök, Murat and Özcerit, Ahmet Turan (2009) Linear Support Vector Machines for HIV-1 Protease Site Detection. In: 1st International Symposium on Sustainable Development, June 9-10, 2009, Sarajevo, Bosnia and Herzegovina.

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Abstract

Several studies have been done for the HIV-1 protease specificity problem by applying machine learning computation techniques recently. In this work, a Linear Support Vector Machine (LSVM) technique has been applied to predict the cleavability of proteins by HIV-1 protease. We used Orthonormal Encoding (OE) extraction technique to map octopeptide sequence inputs. According to simulation outcomes, we have achieved better result, which has a rate of %91.8, compared to earlier studies to predict the cleavability of HIV-1 protease.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > Q Science (General)
Depositing User: Users 4 not found.
Date Deposited: 07 Feb 2012 12:27
Last Modified: 02 Mar 2012 12:42
URI: http://eprints.ibu.edu.ba/id/eprint/514

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