Biomath Genetic Inversion

This-and other BioMath Modules under development-arose from a conference in April, 2005, held at the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) at Rutgers University, organized by Fred Roberts and Margaret Cozzens (both now at DIMACS at Rutgers University). The conference explored methods to establish connections between mathematics and biology, bringing together those who have tried it, those who have made it work on the undergraduate level, and those who know how to get new programs into the schools.

From that conference arose the NSF-sponsored Bio-Math Connection (BMC). It develops innovative classroom materials that highlight connections between mathematics and biology and helps teachers use the materials at various grade levels, in either biology or mathematics classes (or both). The main BMC products are 24 teaching/learning Modules (including this one), together with a book (containing some of the Modules) intended for a one-semester senior-level non-calculus-based course that will satisfy part of state requirements for a fourth year of mathematics or science. These materials are developed primarily for an audience of high school students, but with little adaptation they are suitable for college students too.

BMC is seeking topics, writers, reviewers, and users for further Modules. If you are interested, please contact COMAP

In this module, we will work on the problem of determining how closely related two different species of animals are. Because the genes located on the chromosomes of animals can be represented mathematically as sequences of numbers, we will focus on the related question of how closely related two numerical sequences are.

For example, most people would say that the first two sequences of numbers at left below are much more similar than the two sequences at right below. How can we measure how closely related two given sequences are? What is the significance of this question for biology and for mathematics? These are the questions we explore in this module.