MAIN


©1996-2019.  All Rights Reserved. Online Journal of Bioinformatics . You may not store these pages in any form except for your own personal use. All other usage or distribution is illegal under international copyright treaties. Permission to use any of these pages in any other way besides the  before mentioned must be gained in writing from the publisher. This article is exclusively copyrighted in its entirety to OJB publications. This article may be copied once but may not be, reproduced or  re-transmitted without the express permission of the editors. This journal satisfies the refereeing requirements (DEST) for the Higher Education Research Data Collection (Australia). Linking: To link to this page or any pages linking to this page you must link directly to this page only here rather than put up your own page.


OJBTM

Online Journal of Bioinformatics ©

Volume 16(3): 344-356, 2015.


Machine learning classification for HIV biomarkers.

 

Anubha Dubey.

 

ABSTRACT

 

Dubey A, Machine learning classification for HIV biomarkers, Onl J Bioinform., 16(3): 344-356, 2015. Cytokines IFN-γ, IL-12,IL-7,IL-15 and IL-10 could be used as biomarkers for HIV to predict viral load set-point and subsequent disease progression. Recent studies suggest that combinations of soluble biomarkers may prove more powerful than single factors for predicting HIV disease. Machine learning classifies HIV biomarkers for diagnosis progression and treatment of the disease. Decision tree induction and Naïve bayes algorithms of WEKA software were used to classify and compare CD4+count and IL-10,P24,IFN- biomarkers for diagnosis and screening of HIV/AIDS.

 

Keywords: Cytokines, Interferon, Interleukin, Biomarker, Machine learning.


MAIN

 

FULL-TEXT (SUBSCRIPTION OR PURCHASE TITLE $25USD)