ABSTRACT
As a network that processes information becomes large, and the information is processed in greater quantities and at higher complexity, noise inevitably builds up and can ultimately degrade the useful signal that is the intended result of the computation. We then have to develop approaches to achieve what is known as fault-tolerant information processing, which involves noise control and noise suppression. One notable example of of fault-tolerant information processing is the robustness of many complex processes in cell functions.Presently, we are aware of three primary fault-tolerant information processing paradigms. The first is the analog/digital electronics paradigm of the silicon-chip technology in modern computers. We know how to design such devices and they have been successfully built. Living organisms are the second paradigm: While we obviously know that this paradigm leads to scalability, we do not yet fully understand it, though significant strides have been made in exploring the structure and functioning of biological networks. The third, most recent paradigm, involves massive parallelism: quantum (quantum computing) or ensemble (variants of DNA computing), both in the preliminary research stages.Biochemical computing based on enzymatic reactions8,11-13attempts to process information with biomolecules and biological objects.14-23 However, the information processing paradigm assumed, has, in most cases, been that of ordinary electronics. Indeed, most biochemical computing studies attempt to realize and, most recently, network gates that mimic Boolean digital logic.8,24Networks with computational steps that solely involve bio-chemical processes25,26 are being researched for new technological capabilities: multi-input biosensors with new functionalities,27-29as well as approaches that allow removing the batteries from, and generally reducing the need for, inorganic leads and the electrical power supply for those stages of information processing that occur during biomedical testing, that are used in implantable devices, and for other fast decision-making steps in applications. Futuristic ideas for applications of biochemical logic include more direct brain-computer and body-computer interfacing for both reading out and inputting information, and generally erasing the barrier between inorganic and organic information processing in computer device functioning.
