Train-spotting: building classifiers for microarrays

Lan, Yuxuan, Cawley, G. C. ORCID: https://orcid.org/0000-0002-4118-9095 and Harvey, R. W. ORCID: https://orcid.org/0000-0001-9925-8316 (2003) Train-spotting: building classifiers for microarrays. In: IEEE/INNS International Joint Conference on Artificial Neural Networks, 2003-07-20 - 2003-07-24.

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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)
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Machine learning in computational biology (former - to 2018) Faculty of Science > Research Groups > Computational Biology Faculty of Science > Research Groups > Data Science and AI Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences Faculty of Science > Research Groups > Visual Computing and Signal Processing (former - to 2025) Faculty of Science > Research Groups > Smart Emerging Technologies (former - to 2025) Faculty of Science > Research Groups > Statistics
Depositing User:	Vishal Gautam
Date Deposited:	04 Jul 2011 08:17
Last Modified:	18 Jun 2026 21:08
URI:	https://ueaeprints.uea.ac.uk/id/eprint/23698
DOI:	10.1109/IJCNN.2003.1224037

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