A complex systems approach to computational molecular biology

We report on the continuing research program at the Santa Fe Institute that applies complex systems methodology to computational molecular biology. Two aspects are stressed here: (1) the use of coevolving adaptive neural networks for determining predictable protein structure classifications, and (2) the use of information theory to elucidate protein structure and function. A ``snapshot'' of the current state of research in these two topics is presented, representing the present state of two major research thrusts in the program of Genetic Data and Sequence Analysis at the Santa Fe Institute.