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Abstract：
Among HIV, immune cell and drug, exhibit interactions that are usually not well understood and as a result, cannot be accurately modeled. In this paper, Modeling by AOC is to understand the dynamics of HIV infection and treatment. The use of AOC-by-self-discovery modeling was investigated. AOC-by-self- discovery methods try to adjust the system parameters automatically. To demonstrate the effects of therapies, we design and implement a HIV Computational Lab prototype. HIV Computational Lab is an AOC-based simulation of HIV immune dynamics that is currently being developed in NetLogo. It allows researches to investigate dependencies various immune responses to HIV. The HIV Computational Lab provides a good tool to characterize the process of HIV infection and study HIV drug treatment. © Springer-Verlag Berlin Heidelberg 2007.
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN： 0302-9743
Year： 2007
Volume： 4689 LNBI
Page： 462-469
Language： English
Cited Count：
WoS CC Cited Count： 0
SCOPUS Cited Count：
ESI Highly Cited Papers on the List： 0 Unfold All
WanFang Cited Count：
Chinese Cited Count：
30 Days PV： 4
