title   
  

Short-term HIV therapy response prediction using sequence information

Meydan, Cem and Sezerman, Uğur (2011) Short-term HIV therapy response prediction using sequence information. In: 6th International Symposium on Health Informatics and Bioinformatics, (HIBIT 2011), Izmir, Turkey

[img]PDF - Registered users only until 2012 - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
1053Kb

Abstract

HIV causes 3 million deaths annually. Advancements in medical sciences have enabled us to manage the infection with drug therapies in the recent years. However, HIV-1 has high viral variability and is likely to evolve resistance against these drugs, considering a high correlation between the evolutionary rate and disease progression. It is important to understand the genetic blueprint of the virus and the marker mutations that are linked with disease progression under treatment. For a data set containing clinical patient data at the be-ginning of the therapy, and the reverse transcriptase (RT) and protease (PR) nucleotide sequences of HIV-1 virus, we developed an algorithm to extract a number of features and predict the short term progression of the disease with re-sponse to the therapy and find the important positions within the sequences. The algorithm resulted in around 30 positions that can predict the disease progression with AUC of 0.824 and accuracy of 0.737, better than the standard methods and comparable to the best methods available on such a data.

Item Type:Papers in Conference Proceedings
Subjects:Q Science > Q Science (General)
ID Code:18209
Deposited By:Uğur Sezerman
Deposited On:07 Jan 2012 23:15
Last Modified:07 Jan 2012 23:15

Repository Staff Only: item control page