Title :
Identifying representative drug resistant mutants of HIV reverse transcriptase
Author :
Xiaxia Yu ; Harrison, Robert W. ; Weber, Irene T.
Author_Institution :
Dept. of Comput. Sci., Georgia State Univ., Atlanta, GA, USA
Abstract :
Drug resistance is an important cause in the failure of anti-AIDS treatment. Predictions based on genotype data can guide therapy very efficiently compared to phenotype experiments. We have developed a new algorithm using mean shift clustering to reveal the most representative mutants from a drug resistance database based on our unified protein sequence and 3D structure encoding. This algorithm was tested on genotype-resistance data for mutants of HIV reverse transcriptase and successfully chooses around 300 mutants out of 10K from the whole database.
Keywords :
bioinformatics; diseases; drugs; medical computing; molecular biophysics; patient treatment; proteins; 3D structure encoding; HIV reverse transcriptase mutants; anti-AIDS treatment; drug resistance database; genotype data; genotype-resistance data; mean shift clustering; phenotype experiments; representative drug resistant mutants; representative mutants; unified protein sequence; whole database; Clustering algorithms; Databases; Drugs; Educational institutions; Encoding; Human immunodeficiency virus; Immune system; Delaunay triangulation; Drug resistance prediction; HIV-1 reverse transcriptase; mean shift;
Conference_Titel :
Computational Advances in Bio and Medical Sciences (ICCABS), 2014 IEEE 4th International Conference on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4799-5786-6
DOI :
10.1109/ICCABS.2014.6863934
