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Activity Number:
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349
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 6, 2008 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #300582 |
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Title:
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Differential Equation Modeling of HIV Viral Fitness Experiments: Model Identification, Model Selection, and Multimodel Inference
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Author(s):
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Hongyu Miao*+ and Hulin Wu+ and Carrie Dykes and Lisa M. Demeter
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Companies:
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University of Rochester and University of Rochester and University of Rochester and University of Rochester
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Address:
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Department of Biostatistics and Computational Biology, Rochester, NY, 14642, Department of Biostatistics and Computational Biology, Rochester, NY, 14642,
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Keywords:
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Differential Equation Modeling ; HIV Viral Fitness ; Global Optimization ; Identifiability Analysis ; Model Selection ; Multi-model Inference
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Abstract:
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Many biological processes and systems can be described by a set of differential equation models. However, literature in statistical inference for differential equation models is very sparse. We propose statistical estimation, model selection and multi-model averaging methods for HIV viral fitness experiments in vitro that can be described by a set of nonlinear ordinary differential equations (ODE). The parameter identifiability of the ODE models is also addressed. We apply the proposed methods and techniques to experimental data of viral fitness for HIV-1 mutant 103N. We expect that the proposed modeling and inference approaches for the differential equation models can be widely used for a variety of biomedical studies.
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