Functional information and the emergence of biocomplexity
Robert M. Hazen*†, Patrick L. Griffin*, James M. Carothers‡, and Jack W. Szostak§
*Geophysical Laboratory, Carnegie Institution, 5251 Broad Branch Road NW, Washington, DC 20015-1305; ‡California Institute for Quantitative Biomedical
Research and Berkeley Center for Synthetic Biology, University of California, 717 Potter Street MC 3224, Berkeley, CA 94720-3224; and
§Howard Hughes Medical Institute, Department of Molecular Biology and Center for Computational and Integrative Biology, 7215 Simches
Research Center, Massachusetts General Hospital, Boston, MA 02114-2696
Complex emergent systems of many interacting components, including complex biological systems, have the potential to perform quantifiable functions. Accordingly, we define ‘‘functional information,’’ I(Ex), as a measure of system complexity. For a given system and function, x (e.g., a folded RNA sequence that binds to GTP), and degree of function, Ex (e.g., the RNA–GTP binding energy), I(Ex) log2[F(Ex)], where F(Ex) is the fraction of all possible configurations of the system that possess a degree of function > Ex. Functional information, which we illustrate with letter sequences, artificial life, and biopolymers, thus represents the probability that an arbitrary configuration of a system will achieve a specific function to a specified degree. In each case we observe evidence for several distinct solutions with different maximum degrees of function, features that lead to steps in plots of information versus degree of function.
origin of life artificial life evolution aptamers emergent systems
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