Train-spotting: building classifiers for microarrays
Lan, Y., Cawley, G. C. and Harvey, R. W. (2003) Train-spotting: building classifiers for microarrays. In: Proceedings of the IEEE/INNS International Joint Conference on Artificial Neural Networks (IJCNN-2003), 2003-07-20 - 2003-07-24.
Full text not available from this repository. (Request a copy)Abstract
The problem of extracting spots from DNA microarrays is a problem of considerable scientific and economic utility. In this paper we introduce a new approach based on a scale-space analysis of the image. We augment this with a machine learning system that guides an operator by classifying spots into those that require further attention and those that are already segmented correctly. We compare conventional k-nearest neighbor techniques with generalized linear models and multilayer perceptrons using confidence intervals and McNemar's test.
Item Type: | Conference or Workshop Item (Paper) |
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Faculty \ School: | Faculty of Science > School of Computing Sciences University of East Anglia > Faculty of Science > Research Groups > Computational Biology (subgroups are shown below) > Machine learning in computational biology |
Related URLs: | |
Depositing User: | Vishal Gautam |
Date Deposited: | 04 Jul 2011 08:17 |
Last Modified: | 09 Dec 2020 01:12 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/23698 |
DOI: | 10.1109/IJCNN.2003.1224037 |
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