By Topic

HIV-1 Coreceptor Usage Prediction via Indexed Local Kernel Smoothing Methods and Grid-Based Multiple Statistical Validation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Fanti, I. ; Univ. of Roma TRE, Rome ; Prosperi, M.C. ; Ulivi, G. ; Micarelli, A.

Human immunodeficiency virus type 1 (HIV-1) isolates differ in their use of coreceptors to enter target cells. This has important implications for both viral pathogenicity and susceptibility to entry inhibitors under development. Predicting HIV-1 coreceptor usage on the basis of sequence information is a challenging task due to the high variability of the HIV-1 genome. We present an efficient local smoothing kernel method, enhanced with a BLAST-based distance function, implemented by usage of multithreading grid procedures and indexing. Robust validation of the model is achieved through multiple cross-validation, along with statistical comparisons of results for performance assessment.

Published in:

Computer-Based Medical Systems, 2007. CBMS '07. Twentieth IEEE International Symposium on

Date of Conference:

20-22 June 2007