Biomedical subjects

K P Zauner

Publications and source records attributed to K P Zauner.

3 recordsLinked to original sources

PubMed2000

Enzymatic pattern processing.

A table-top prototype has been constructed that uses the enzyme malate dehydrogenase to recognize input signal patterns. The device is controlled by the enzyme in response to injection of Mg2+ used as a signaling substance. Output is monitored spectroscopically. If Mg2+ is injected along either of two signal lines (i.e., if the input signal pattern is 10 or 01) the device emits an output of 1. Injection along neither or both lines results in an output of 0. The enzyme in effect is used as a transform that converts the linearly inseparable exclusive- or problem into a linearly separable problem.

Calcium↗

PubMed1998

DNA as a vehicle for the self-assembly model of computing.

A DNA version of the self-assembly model of computing, feasible using currently available laboratory techniques, is proposed. Input signals are coded into unmethylated and methylated oligonucleotides which then hybridize with a backbone that contains complementary sequences. Different input signal patterns are thus represented as DNA duplexes with distinctly different conformational dynamics, in particular different equilibria of B and Z DNA. The pattern classification activity of the system is mediated by the interactions that lead to the secondary structural organization. Circular dichroism may be used for readout.

Computer Simulation↗

PubMedDate not supplied

Enzymatic computing.

The conformational dynamics of enzymes is a computational resource that fuses milieu signals in a nonlinear fashion. Response surface methodology can be used to elicit computational functionality from enzyme dynamics. We constructed a tabletop prototype to implement enzymatic signal processing in a device context and employed it in conjunction with malate dehydrogenase to perform the linearly inseparable exclusive-or operation. This shows that proteins can execute signal processing operations that are more complex than those performed by individual threshold elements. We view the experiments reported, though restricted to the two-variable case, as a stepping stone to computational networks that utilize the precise reproducibility of proteins, and the concomitant reproducibility of their nonlinear dynamics, to implement complex pattern transformations.

Calcium↗