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Autonomous Experimentation: Coupling Active Learning with Computer Controlled Microfluidics (abstract)

Autonomous Experimentation: Coupling Active Learning with Computer Controlled Microfluidics (abstract)
Autonomous Experimentation: Coupling Active Learning with Computer Controlled Microfluidics (abstract)
The interactions of biomolecular substrates, such as networks of enzymes, exhibit behaviours that could allow for new modes of information processing. Information processing is not required to work within physiological conditions, therefore the contribution of existing knowledge about enzyme interactions is limited. New knowledge about the interactions of enzymes can only be obtained experimentally. However, the high dimensionality of the parameter spaces mean that the resources available are limited compared to the size of the space to explore. Often this can leave at most a handful of experiments per parameter dimension. Additionally, the validity of experimentally obtained observations are not guaranteed, particularly in the biological domain where experimental error can produce observations not representative of the true behaviour. By combining active learning techniques with an automated lab-on-chip platform, we are working towards a fully autonomous machine. This machine will provide effective resource usage, achieved through both minimising the number of experiments required to be performed and by reducing the chemical resources consumed in each experiment.
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) Autonomous Experimentation: Coupling Active Learning with Computer Controlled Microfluidics (abstract). Active Learning and Experimental Design Workshop, Sardinia, Italy. (In Press)

Record type: Conference or Workshop Item (Other)

Abstract

The interactions of biomolecular substrates, such as networks of enzymes, exhibit behaviours that could allow for new modes of information processing. Information processing is not required to work within physiological conditions, therefore the contribution of existing knowledge about enzyme interactions is limited. New knowledge about the interactions of enzymes can only be obtained experimentally. However, the high dimensionality of the parameter spaces mean that the resources available are limited compared to the size of the space to explore. Often this can leave at most a handful of experiments per parameter dimension. Additionally, the validity of experimentally obtained observations are not guaranteed, particularly in the biological domain where experimental error can produce observations not representative of the true behaviour. By combining active learning techniques with an automated lab-on-chip platform, we are working towards a fully autonomous machine. This machine will provide effective resource usage, achieved through both minimising the number of experiments required to be performed and by reducing the chemical resources consumed in each experiment.

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Lovell10AutExpActLearnAbst.pdf - Accepted Manuscript
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More information

Accepted/In Press date: 12 March 2010
Additional Information: Event Dates: 16 May 2010
Venue - Dates: Active Learning and Experimental Design Workshop, Sardinia, Italy, 2010-05-16
Organisations: Agents, Interactions & Complexity, Electronic & Software Systems

Identifiers

Local EPrints ID: 270979
URI: http://eprints.soton.ac.uk/id/eprint/270979
PURE UUID: a6973a75-9d89-488c-a262-d40f058443c6

Catalogue record

Date deposited: 04 May 2010 11:47
Last modified: 14 Mar 2024 09:20

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Contributors

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

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