Selectivity of Resins with Guanidy Groups Towards Dicyanoaurate Anions

Proteins and nucleic acids constitute a vast potential reservoir of pattern recognizers that operate on the basis of shape complementarity. It is possible to construct models of computing in which these shape-based interactions contribute directly to recognition of signal patterns at the device (or cell) level. The input-output transform is molded by variationselection evolution. Such models provide clues as to the organizational features that enable biomolecular matter to acquire nonevolutionary modes of problem solving through the evolutionary process. The requisite organizations are characterized by a high dimensionality that allows them to simultaneously exhibit aspects of context-sensitivity and contextindependence.