Recombination is a major force in HIV evolution, but it is hard to study. It is particularly challenging to identify intra-host recombination between closey related viruses. The Investigators therefore propose new mathematical methods to study recombination in HIV and reticulate evolution generally. Each method will address biologically relevant questions about HIV infection and epidemiology. This proposal contributes to topological data analysis (TDA), a new quantitative approach to find structure in large datasets. The Investigators recently found that TDA provides rich information about evolving populations and is useful for detecting recombination. Objectives:
Aim 1 : Create new methods in TDA to characterize recombination;
Aim 2 : Apply these methods to HIV evolution;
Aim 3 : Build software tools for the research community.
Aims will proceed iteratively, and preliminary results enable Aims 1 & 2 to begin immediately. The high-level strategy for each evolutionary scenario is: (1) Simulate specific scenario, (2) Discover topological statistic(s) corresponding to biological quantities of interest, (3) Validate statistic's power to estimate biological quantity in simulation, (4) Explain/Prove why the statisti is a valid estimator, (5) Apply statistic to biological/clinical questions.

Public Health Relevance

Recombination is a major force in HIV evolution and disease progression, but it is hard to study. The Investigators therefore propose new mathematical methods to study recombination. These methods will advance the current state of topological data analysis, a growing area in the study of large datasets. Investigators will apply these methods to open questions about HIV infection and epidemiology.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM117591-02
Application #
9119841
Study Section
Special Emphasis Panel (ZGM1)
Program Officer
Ravichandran, Veerasamy
Project Start
2015-08-03
Project End
2019-04-30
Budget Start
2016-05-01
Budget End
2017-04-30
Support Year
2
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
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