Information theory and entropy methods are becoming powerful tools in biology, from the level of individual cells, to whole ecosystems, to experimental design, model-building, and the measurement of biodiversity. The aim of this investigative workshop is to synthesize different ways of applying these concepts to help systematize and unify work in biological systems. Early attempts at "grand syntheses" often misfired, but applications of information theory and entropy to specific highly focused topics in biology have been increasingly successful. In ecology, entropy maximization methods have proven successful in predicting the distribution and abundance of species. Entropy is also widely used as a measure of biodiversity. Work on the role of information in game theory has shed new light on evolution. As a population evolves, it can be seen as gaining information about its environment. The principle of maximum entropy production has emerged as a fascinating yet controversial approach to predicting the behavior of biological systems, from individual organisms to whole ecosystems. This investigative workshop will bring together top researchers from these diverse fields to share insights and methods and address some long-standing conceptual problems.
NIMBioS Investigative Workshop Information and Entropy
Topic: Information and entropy in biological systems
Meeting dates: April 8-10, 2015
Location: NIMBioS at the University of Tennessee, Knoxville
• John Baez, Mathematics, Univ. of California, Riverside
• Marc Harper, Educational and biotechnology consultant
• John Harte, Environmental Science, Policy and Management, Univ. of California, Berkeley