Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/4743
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dc.contributor.authorFraser, K-
dc.contributor.authorO'Neill, P-
dc.contributor.authorWang, Z-
dc.contributor.authorLiu, X-
dc.date.accessioned2011-02-17T09:57:00Z-
dc.date.available2011-02-17T09:57:00Z-
dc.date.issued2004-
dc.identifier.citationIn Proceedings of the 8th International Conference on Control, Automation, Robotics and Vision, 2:1061-1066, Kunming, China, Dec. 6-9, 2004.en_US
dc.identifier.isbn0-7803-8653-1-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/4743-
dc.descriptionCopyright [2004] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.en_US
dc.description.abstractIn the past decade computational biology has come to the forefront of the public's perception with advancements in domain knowledge and a variety of analysis techniques. With the recent completion of projects like the human genome sequence, and the development of microarray chips it has become possible to simultaneously analyse expression levels for thousands of genes. Typically, a slide surface of less than 24 cm2, receptors for 30,000 genes can be printed, but currently the analysis process is a time consuming semi-autonomous step requiring human guidance. The paper proposes a framework, which facilitates automated processing of these images. This is supported by real world examples, which demonstrate the technique's capabilities along with results, which show a marked improvement over existing implementations.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectBiology computingen_US
dc.subjectCellular arraysen_US
dc.subjectGeneticsen_US
dc.subjectMedical image processingen_US
dc.subjectSequencesen_US
dc.titleCopasetic analysis: Automated analysis of biological gene expression imagesen_US
dc.typeConference Paperen_US
dc.identifier.doihttp://dx.doi.org/10.1109/ICARCV.2004.1468990-
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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