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2009 Summer Program in Mathematical Biology for Undergraduates
(June 22-July 2, 2009)

This program consists of two parts: (a) two weeks of introductory lectures plus short projects and a computer lab, and (b) a summer long research experience (6 weeks to be followed immediately after the 2 weeks) devoted to projects in the interface of mathematics, statistics, and biological sciences.

Program Leaders:

  • Dennis Pearl: Statistical Phylogenetics (Monday, June 22)
  • Michael Rempe: Mathematical Neuroscience (Tuesday, June 23)
  • Joe Verducci: Chemogenomics (Wednesday, June 24)
  • Kate Calder: Environmental Statistics (Thursday, June 25)
  • Kun Huang: Bioinformatics (Friday, June 26)

Week 1: June 22 - 26, 2009

Monday 6/22: Statistical Phylogenetics
8:30am Registration and welcome
9:00am-10:00am Dennis Pearl: Statistical Phylogenetics I: Background, Sequence Alignment, Parsimony, Maximum Likelihood
10:00am-10:30am Coffee break
10:30am-11:30am Dennis Pearl: Statistical Phylogenetics II: Optimization algorithms, the Bootstrap, Bayesian Phylogenetics
11:30am-2:00pm Lunch break
2:00pm-4:00pm Computer lab: Lori Hoffman
Software: PHYLIP, GARLI, & MrBayes
Tuesday 6/23: Mathematical Neuroscience
9:00am-10:00am Michael Rempe: Introduction to Neuroscience
10:00am-10:30am Coffee break
10:30am-11:30am Michael Rempe: Mathematical Modeling and Neuroscience: Hodgkin-Huxley models and dynamical systems
11:30am-2:00pm Lunch break
2:00pm-4:00pm Computer lab
Software: XPPAUT, MATLAB
Wednesday 6/24: Chemogenomics
9:00am-10:00am Paul Blower: Introduction to Chemogenomics: chemical structures, bioassays, gene expression
10:00am-10:30am Coffee break
10:30am-11:30am Joe Verducci: Statistical Methods in Chemogenomics: measures of correlation, data mining for association
11:30pm-2:00pm Lunch break
2:00pm-4:00pm Computer lab with GRA
Software: R, Tau-path programs
Thursday 6/25: Environmental Statistics
9:00am-10:00am Kate Calder: Environmental Statistics I: Environmental Data, Exploratory Analyses, Statistical Modeling
10:00am-10:30am Coffee break
10:30am-11:30am Kate Calder: Environmental Statistics II: Statistical Methods in Environmental Health, Introduction to Bayesian Hierarchical Modeling
11:30pm-2:00pm Lunch break
2:00pm-4:00pm Computer lab: Candace Berrett
Software: R
Friday 6/26
9:00am-10:00am Kun Huang: Bioinformatics - microarray data analysis I: Background, normalization, data visualization
10:00am-10:30am Coffee break
10:30am-11:30am Kun Huang: Bioinformatics - microarray data analysis II: Data clustering, gene network inference, gene set enrichment analysis
11:30am-2:00pm Lunch break
2:00pm-4:00pm Computer lab: Jie Zhang
Software: Matlab (w/ Bioinformatics and Statistics toolboxes), R (w/ Bioconductor) and DAVID (online tool)

Week 2: Lab Tours and Team Projects

Tuesday 6/30
1:00pm Joe Travers' Neuroscience Lab
Wednesday 7/1
1:00pm Museum of Biological Diversity 1315 Kinnear Road - tour by museum director John Wenzel
2:00pm Aquatics Ecology Laboratory of Elizabeth Marschall at 1314 Kinnear Road
Thursday 7/2: Team Projects
12:00-12:30pm Students set up posters and prepare for presentations
12:30-1:00pm Poster viewing
1:00-3:30pm Oral presentations

REU Presentations

Friday 8/14
   

Team Projects: June 29 - July 2, 2009

Dennis Pearl: The phylogenetics project will explore the evolution and global spread of the swine flu (H1N1) virus and how this evolution may be related to the clinical course of the disease.

Michael Rempe: The neuroscience project will explore a mathematical model of human sleep and investigate the effects of jet-lag on subsequent sleep timing.

Joe Verducci: The chemogenomics project will search the NCI database for combinations of genes that may affect the chemosensitivity of cancer cell-lines to a class of anti-cancer drugs.

Kate Calder: The environmental statistics project will examine regional differences in the health effects associated with particulate matter exposure using data from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS).

Kun Huang: The bioinformatics project will explore the gene co-expresion network in cancers using multiple microarray data sets for identifying new cancer biomarkers to predict prognosis.