Preparing Researchers for the Quantitative Biology of the Future

Saturday, 14 February 2015: 8:30 AM-11:30 AM
Room LL21F (San Jose Convention Center)
Advances in quantification of biology and medicine will soon render obsolete researchers and practitioners who are not fluent in quantitative assessment of data and mechanistic understanding of biological and medical systems through modeling and simulation. How can graduate programs across the life sciences create and deliver content and learning practices to prepare students to evolve with quantitative advances and their translational impact? The consensus that graduate programs in the biological, medical, and health sciences should include quantitative skills in the training of researchers, clinicians, and health care deliverers has yet to coalesce on statistical and mathematical content, use of software, and ways to integrate with existing curricula and
expertise. Because of cultural mismatches within the university, successful programs must address teaching load disparities in biological, mathematical, and medical departments; use of focused modules or full courses; individual or team teaching; and rewards for teaching and curriculum innovation. Stakeholder disciplines include genomics, bioinformatics, molecular and systems biology, medicine, statistics, mathematics, and computer science. Speakers, experts in these areas and in STEM education and evaluation, will address the justifications and challenges for quantitative curricular reform. A final panel discussion will identify national actions in the U.S. to overcome cultural obstacles, share methods, and build consensus.
Frederick R. Adler, University of Utah
M. Gregory Forest, University of North Carolina
Bruce M. Alberts, University of California
Vicki L. Chandler, Gordon and Betty Moore Foundation
Training Biologically Expert Data Scientists Within Today's Academic Culture
James P. Keener, University of Utah
Building Effective Collaborations in Quantitative Biology
Susan R. Singer, Carleton College
Preparing Future Quantitative Biologists
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