Computational methods for the design of effective therapies against drug resistant HIV strains.
The development of drug resistance is a major obstacle to successful treatment of HIV infection. The extraordinary replication dynamics of HIV facilitates its escape from selective pressure exerted by the human immune system and by combination drug therapy. We have developed several computational methods whose combined use can support the design of optimal antiretroviral therapies based on viral genomic data.
Beerenwinkel
Niko
N
Department of Mathematics, University of California, Berkeley, CA, USA. niko@math.berkeley.edu
Sing
Tobias
T
Lengauer
Thomas
T
Rahnenführer
Jörg
J
Roomp
Kirsten
K
Savenkov
Igor
I
Fischer
Roman
R
Hoffmann
Daniel
D
Selbig
Joachim
J
Korn
Klaus
K
Walter
Hauke
H
Berg
Thomas
T
Braun
Patrick
P
Fätkenheuer
Gerd
G
Oette
Mark
M
Rockstroh
Jürgen
J
Kupfer
Bernd
B
Kaiser
Rolf
R
Däumer
Martin
M
D003628:Database Management Systems; D016208:Databases, Factual; D015195:Drug Design; D004346:Drug Information Services; D024882:Drug Resistance, Viral / Q000187:drug effects / Q000235:genetics; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D015316:Genetic Therapy; D015658:HIV Infections / Q000188:drug therapy*; D006801:Humans; D014765:Viral Vaccines / Q000008:administration & dosage* / Q000235:genetics*
D014765:Viral Vaccines