Supporting Scientific Collaboration Online SCOPE Workshop at San Diego Supercomputer Center March 19-22, 2008.

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Presentation transcript:

Supporting Scientific Collaboration Online SCOPE Workshop at San Diego Supercomputer Center March 19-22, 2008

Workshop Structure Overview Introductions to working with: –a Problem Space –an Investigative Case –OERCommons –Visualization tools –CaseIT –Planting Science 2 small group projects w/ presentations –Integrate OER, E-science, and/or Web 2.0 resources into a teaching project of your choice. –Describe ways you will build and/or teach with collaborative tools and resources.

Investigations of HIV-1 Env Evolution Evolutionary Bioinformatics: Microbial analyses from sequence to structure to function to ecology SCOPE Workshop at SDSC March 19-22, 2008

1. Virus docks with receptors on host cell (CD4 + co-receptor) 2. Reverse transcription: viral RNA  DNA 3. Viral DNA inserts into host’s DNA 4. Viral RNA transcribed & proteins assembled 5. New virions bud from host cell, killing it Life Cycle of HIV

HIV Virus

The HIV Genome

HIV env Gene

gp120 V3 region sequence Nucleic Acid Sequence CTAGCAGAAGAAGAGGTAGTAATTAGATCTGCCAATTTCACAGACAATGCTAAAATCATAATAGTACAGC TGAATGCATCTGTAGAAATTAATTGTACAAGGCCCAACAACAATACAAGAAAAGGTATACATATAGGACC AGGGAGAGCATTTTATGCAACAGGAGAAATAATAGGAGATATAAGACAAGCACATTGTAACATTAGTAGA GAAAAATGGAATAATACTTTAAACCAGGTAGTTACAGAATTAAGGGAACAATTTGGGAATAAAACAATAA CCTTTAATCACTCCTCAGGAGGGGACCCAGAAATTGTAATGCACAGTTTTAATTGTGGAGGGGAATTTTT CTATTGTAAT Amino Acid Sequence LAEEEVVIRSANFTDNAKIIIVQLNASVEINCTRPNNNTRKGIHIGPGRAFYATGEIIGDIRQAHCNISR EKWNNTLNQVVTELREQFGNKTITFNHSSGGDPEIVMHSFNCGGEFFYCN

gp 120 Structure

The Markham et al.HIV-1 env Sequence Dataset Longitudinal study of 15 HIV+ patients from Baltimore Patients came in at 6-month intervals (“visits”) over 4-year period Focused on the 3rd variable loop of the env gene (285 bp) Each visit: sampled ~10 viral sequences and measured CD4 levels Rich data set for analyzing patterns of HIV evolution and their correlation with rates of T-cell decline

Summary of the data set Subjects: 15 Number of visits: 3-9 Number of clones per visit: 2-18 Total number of sequences available: 666 CD4 cell counts for each visit

Possible Investigations What is the pattern of HIV evolution within an individual? –Do the number of clones over time change in any regular way? –Do certain clones appear to survive (leave descendents) over time while other disappear (go extinct)?

Possible Investigations What is the pattern of HIV evolution within the env sequence? –Are there particular positions in the sequence that are more or less likely to mutate? –Are there different rates of synonymous (silent) and non-synonymous mutations?

User Web Browser Output to User User Input Format Translator, Query Engine and Program Driver Workbench Server Results to User User Instructions and queries Application Programs (May have varying interfaces and be written in different languages) Results Instructions Information Sources (May be of varying formats) Information Queries NCSA Computational Biology Group The NCSA Information Workbench - An Architecture for Web-Based Computing