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
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26 June 2010
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, .
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.
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LovellC10CharEnzTowArtExp.pdf
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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
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Date deposited: 05 Jul 2010 13:42
Last modified: 14 Mar 2024 09:28
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Contributors
Author:
Chris Lovell
Author:
Gareth Jones
Author:
Steve Gunn
Author:
Klaus-Peter Zauner
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