2 options
Bayesian statistical models for HIV evolution.
- Format:
- Book
- Thesis/Dissertation
- Author/Creator:
- Braunstein, Alexander Fredric.
- Language:
- English
- Subjects (All):
- Bioinformatics.
- Statistics.
- 0463.
- 0715.
- Penn dissertations--Statistics.
- Statistics--Penn dissertations.
- Local Subjects:
- Penn dissertations--Statistics.
- Statistics--Penn dissertations.
- 0463.
- 0715.
- Physical Description:
- 104 pages
- Contained In:
- Dissertation Abstracts International 70-10B.
- System Details:
- Mode of access: World Wide Web.
- text file
- Summary:
- Statistical models provide an important mechanism for describing and understanding sequence evolution, such as the escape response of a viral population under a particular therapy. We present a new hierarchical Bayesian model that incorporates spatially varying mutation and recombination rates into a coalescent framework for sequence evolution. Focusing on evolutionary responses to therapy, we maintain separate parameters for treatment and control groups, which allows us to estimate treatment effects explicitly. Our approach is used to investigate sequence evolution at the nucleotide level of HIV populations exposed to a recently developed antisense gene therapy, as well as a more conventional drug therapy. Detection of biologically relevant signals in both studies and recovery of true mutation and recombination rates in extensive simulation studies demonstrate the effectiveness of our method.
- Notes:
- Thesis (Ph.D. in Statistics) -- University of Pennsylvania, 2009.
- Source: Dissertation Abstracts International, Volume: 70-10, Section: B, page: 6317.
- Adviser: Shane Jensen.
- Local Notes:
- School code: 0175.
- ISBN:
- 9781109428247
- Access Restriction:
- Restricted for use by site license.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.