The University of Southampton
University of Southampton Institutional Repository

Characterising Enzymes for Information Processing: Towards an Artificial Experimenter

Characterising Enzymes for Information Processing: Towards an Artificial Experimenter
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.
978-3-642-13522-4
81-92
Springer Berlin, Heidelberg
Lovell, Chris
1ac8eed7-512f-4082-a7ab-75b5e4950518
Jones, Gareth
469d05ca-944e-43cd-91bc-12074c13848e
Gunn, Steve
306af9b3-a7fa-4381-baf9-5d6a6ec89868
Zauner, Klaus-Peter
c8b22dbd-10e6-43d8-813b-0766f985cc97
Lovell, Chris
1ac8eed7-512f-4082-a7ab-75b5e4950518
Jones, Gareth
469d05ca-944e-43cd-91bc-12074c13848e
Gunn, Steve
306af9b3-a7fa-4381-baf9-5d6a6ec89868
Zauner, Klaus-Peter
c8b22dbd-10e6-43d8-813b-0766f985cc97

Lovell, Chris, Jones, Gareth, Gunn, Steve and Zauner, Klaus-Peter (2010) Characterising Enzymes for Information Processing: Towards an Artificial Experimenter. In, 9th International Conference on Unconventional Computation. Springer Berlin, Heidelberg, pp. 81-92.

Record type: Book Section

Abstract

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.

Text
LovellC10CharEnzTowArtExp.pdf - Version of Record
Download (477kB)

More information

Published date: 26 June 2010
Organisations: Agents, Interactions & Complexity, Electronic & Software Systems

Identifiers

Local EPrints ID: 271344
URI: http://eprints.soton.ac.uk/id/eprint/271344
ISBN: 978-3-642-13522-4
PURE UUID: bfdfef89-9047-4e24-933c-5235749ef481

Catalogue record

Date deposited: 05 Jul 2010 13:42
Last modified: 14 Mar 2024 09:28

Export record

Contributors

Author: Chris Lovell
Author: Gareth Jones
Author: Steve Gunn
Author: Klaus-Peter Zauner

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×