Characterising Enzymes for Information Processing: Towards an Artificial Experimenter

The information processing capabilities of many proteins are currently unexplored. The complexities and high dimensional parameter spaces make their investigation impractical. Difficulties arise as limited resources prevent intensive experimentation to identify repeatable behaviours. To assist in this exploration, computational techniques can be applied to efficiently search the space and automatically generate probable response behaviours. Here an artificial experimenter is discussed that aims to mimic the abilities of a successful human experimenter, using multiple hypotheses to cope with the small number of observations practicable. Coupling this approach with a lab-on-chip platform currently in development, we seek to create an autonomous experimentation machine capable of enzyme characterisation, which can be used as a tool for developing enzymatic computing.

• Type: Journal
• Year: 2010
• Where: UC
• Authors: Chris Lovell, Gareth Jones, Steve R. Gunn, Klaus-Peter Zauner
• Keywords: Applied Computing, Enzyme Characterisation, Probable Response Behaviours, Repeatable Behaviours, UC 2010