This project was prepared as part of a BioQUEST faculty development workshop entitled ASM/BioQUEST Bioinformatics Institute at American Society for Microbiology in March 2006. The BioQUEST Curriculum Consortium is committed to the reform of undergraduate biology instruction through an emphasis on engaging students in realistic scientific practices. This approach is sometimes characterized as an inquiry driven approach and is captured in BioQUEST's three P's (problem-posing, problem-solving, and peer-persuasion). As part of this workshop groups of faculty were encouraged to initiate innovative curricular projects. We are sharing these works in progress in the hope that they will stimulate further exploration, collaboration and development. Please see the following links for additional information:

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Do HIV+ Rapid Progressors Show More Divergenece than Non-Progressors?
 
 
Authors          Audiences          Overview           Materials          Resources           Future Directions
 

 


Authors

Alix Darden
The Citadel


Karen Klyczek
University of Wisconsin-River Falls


Mark Bergland
University of Wisconsin-River Falls

Susan Godfrey
University of Pittsburgh

Karl Beres
Ripon College

 
   
 


Possible Audiences:

Other bioinformatics workshop participants  

 
 


Brief Overview:

Analysis of HIV env sequence data from Bedrock dataset to test the hypothesis that the viral population of rapid progressors to AIDS may be more complex than that of non-progressors.  

 
   
 


Project Materials:

HIV env nucleotide sequences from patient virus samples collected at 6 month intervals during clinic visits over a period of 3 to 6 years  

 
 


Resources and References:

(1) Markham, R.B. et al. (1998) P.N.A.S. USA 95:12568, source of our dataset and the source of the genome map used in the poster. (2) "Evolutionary Bioinformatics: Microbial analyses from sequence to structure to function to ecology", ASM March 2-5, 2006 workshop materials, including the Markham paper et al with dataset in print form and the dataset in silico, and awsome instructors. (3) Sequence analysis tools provided by the Biology Workbench http://workbench.sdsc.edu.  

 
   
 


Future Directions:

Were ruminating on how to make a quantitative analysis of whether the distance matrices generated by the multiple sequence alignments track with differences in T-cell counts among the progressors & non-progressors in our dataset.  

 
 


Attachments


- HIV_KK.ppt