Parameter Estimation for Dynamic Biological Models
Topic: Parameter Estimation for Dynamic Biological Models
Meeting dates: May 19-21, 2014
Location: NIMBioS at the University of Tennessee, Knoxville
Ariel Cintron-Arias, Mathematics and Statistics, East Tennessee State Univ.
Marisa Eisenberg, Epidemiology and Mathematics, Univ. of Michigan
Paul Hurtado, Mathematical Biosciences Inst., Aquatic Ecology Laboratory, The Ohio State Univ.
Objectives: Modeling biological data requires powerful mathematical and statistical tools and techniques. This tutorial is for biologists interested in doing statistics with more complex non-linear models of their data and for mathematicians interested in learning how to apply their modeling skills to the unique demands of real dynamic biological data. Methods for parameter estimation that will be taught include maximum likelihood and ordinary least squares. Additional tools of model identifiability and sensitivity analysis will be covered. Through a mixture of introductory instruction and hands-on computer-based learning, participants will learn software and tools they can use for biological data. Familiarity with simple differential equation models or difference equation models is a prerequisite.
Presentations were available for viewing via live streaming during the workshop. A live chat took place via Twitter with the hashtag #parameterTT. A playlist of archived videos will not be available for this tutorial.
Summary Report. TBA
Evaluation report (PDF)
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