Teaching Mathematics and its Applications Advance Access published online on April 24, 2008
Teaching Mathematics and its Applications, doi:10.1093/teamat/hrn003
‘Model your genes the mathematical way’—a mathematical biology workshop for secondary school teachers
Address for correspondence: Paola Vera-Licona, BioMaPS Institute, Rutgers University, 110 Frelinghuysen Road, Piscataway, NJ 08854, USA. Tel: (732) 445-3160; Fax: (732) 446-3168; E-mail: mveralic{at}math.rutgers.edu
Submitted October 2007; accepted March 2008
This article describes a mathematical biology workshop given to secondary school teachers of the Danville area in Virginia, USA. The goal of the workshop was to enable teams of teachers with biology and mathematics expertise to incorporate lesson plans in mathematical modelling into the curriculum. The biological focus of the activities is the lactose operon in Escherichia coli, one of the first known intracellular regulatory networks. The modelling approach utilizes Boolean networks and tools from discrete mathematics for model simulation and analysis. The workshop structure simulated the team science approach common in today's practice in computational molecular biology and thus represents a social case study in collaborative research. The workshop provided all the necessary background in molecular biology and discrete mathematics required to complete the project. The activities developed in the workshop show students the value of mathematical modelling in understanding biochemical network mechanisms and dynamics. The use of Boolean networks, rather than the more common systems of differential equations, makes the material accessible to students with a minimal mathematical background.
High school students can be exposed to the excitement of mathematical biology from both the biological and mathematical point of view. Through the development of instructional modules, high school biology and mathematics courses can be joined without having to restructure the curriculum for either subject. The relevance of an early introduction to mathematical biology allows students not only to learn curriculum material in a innovative setting, but also creates an awareness of new educational and career opportunities that are arising from the interconnections between biological and mathematical sciences.
The materials used in this workshop are available at a website created by the directors: http://polymath.vbi.vt.edu/mathbio2006/.
Ana Margarida Martins and Paola Vera-Licona contributed equally to this work.
Ana Margarida Martins is a Research Associate at Virginia Bioinformatics Institute (VBI). She works as a Yeast Systems Biologist in the Biochemical Profiling Group. Previously, she was a Postdoctoral Research Associate at VBI in the Biochemical Networks Modeling Group. She has been working in several aspects of yeast systems biology, including the yeast response to oxidative stress, and the bottom-up modelling of the yeast pentose phosphate pathway. Recently, she has dedicated more research time to metabolomics studies in yeast cells and human cancer cells. Ana Martins obtained her BSc degree in Biochemistry from the University of Lisbon, Portugal in 1994 and her PhD in Biochemistry/Enzymology from the same University in 2000.
Paola Vera-Licona is a postodoctoral fellow at the BioMaPS Institute jointly with DIMACS and the Mathematics Department at Rutgers University. Her research area is mathematical and computational biology, with a particular interest on the modelling and simulation of biological networks such as gene regulatory networks and brain response networks. She has worked mainly on top-bottom modelling approaches with the use of computational algebra, evolutionary algorithms and combinatorics tools. Together with her research in Mathematical Biology, she has been involved along her whole career with different mathematics education projects and outreach activities in Mexico and the US. Paola Vera-Licona received her BSc degree in Mathematics from the Universidad Nacional Autonoma de Mexico (UNAM) in 2001 and her MS (in 2003) and PhD (in 2007) in Mathematics at Virginia Tech.
Reinhard Laubenbacher is a professor at the Virginia Bioinformatics Institute and a Professor of Mathematics at Virginia Tech. His research area is computational systems biology, in particular modelling and simulation of biological networks. Application areas include yeast systems biology, computational immunology and cancer systems biology. He received his PhD in Mathematics from Northwestern University in 1995.