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Individual & Population Variation in Biology, Medicine, & Society

Diverse researchers—from biology, medicine, statistics, nutrition, sociology, public health, anthropology, athletics, and more—will be collaborating across traditional research boundaries to investigate the causes and consequences of individual and popula

Gene Variation, Disease, and Personalized Medicine


Description: What are the challenges in analyzing and integrating big data from -omics technologies and clinical datasets, electronic health records? Objectives/Deliverables: 1) Hands on experience with handling big datasets (Hackathon); 2) Analysis of datasets that could feed into grant applications. (eg TOPMed, Alzheimer's GWAS?); 3) Review paper illustrating the technical and analytical challenges in doing these kinds of integrations, to be submitted for publication.

Working Group Agenda, Notes & Resources

Working Group Schedule & Locations

Mon, 5/15  4 hr. kickoff meeting (10-12, break for lunch, 1-3)

  • 10-12pm: WEL 3.134

  • 1-3 pm: FNT 1.104

Tue-Thu, 5/16-5/18     10-12 each day

  • Tue the 16th: POB 2.404B

  • Wed the 17th: WEL 3.134

  • Thur the 18th: WEL 3.134

Mon-Wed, 5/22-5/24   1-3

  • Mon 22nd: PAT 142

  • Tue 23rd: FNT 1.104

  • Wed 24th: PAT 142

Topics to address:

  1. Publicly available datasets – genomics and clinical
  2. Creating/managing big data sets – QC, missing, merging phenotype and genotype data
  3. Computing needs/resources
  4. Multi-omics approaches
  5. “Untrained” statistical methodology (e.g., machine learning, AI, Bayesian networks)

Potential components of a review paper that would identify:

  1. Challenges
  2. Opportunities
  3. Needs
  4. Next steps

Recommended Readings & Resources

Institute Coordinator


Postdoctoral Fellow, Department of Integrative Biology
College of Natural Sciences
Personal Page 
Hofmann Lab


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Hannah Chapman Tripp
Life Sciences Library
MAI 224

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