Applications in Biology, Dynamics, and Statistics

Advances in computational algebra in the past few years have lead to the use of algebraic geometry to study problems in biology, dynamics, and statistics. Some highlights of these new applications include: algebraic techniques for studying and solving the likelihood equations for discrete random variables in statistics; Groebner basis techniques to generate random walks on high dimensional contingency tables and their applications in disclosure limitation; the use of toric geometry to study the dynamics of chemical systems; the algebraic tools for producing invariants of Markov models in phylogeny and their applications in phylogenetic tree recovery; and the application of tropical geometry for parametric sequence alignment in genomics.

The focus of this workshop is on these relatively new applications of algebraic geometry where the full scope of the techniques are still developing. We hope to bring together a broad range of researchers in both algebraic geometry and applied science. A key aim is to establish a bridge between mathematicians wishing to learn more about these applications and to expose new algebraic tools to researchers in industry and academia.