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Selection of more than one gene at a time for cancer prediction from gene expression data

Selection of more than one gene at a time for cancer prediction from gene expression data
Selection of more than one gene at a time for cancer prediction from gene expression data
A new gene selection method capable of selecting more than one gene at a time is introduced. This characteristic contrasts it with almost all known methods assuming that there are no interactions between genes. The only exception is the pairwise gene selection method recently proposed by Bø and Jonassen [3]. Motivated by this method, we compare it and ours. Classification into healthy tissue and cancerous tumour is studied, where gene selection finds gene subsets well suitable for discriminating between these two classes. © 2006 i6doc.com publication. All rights reserved.
551-556
Okun, O.
10ebb8b0-d8df-4334-9321-1c88c284fa05
Zagoruiko, N.
2540f602-9f8b-41e7-9785-28ea207fdbd8
Alves, A.
87b9179e-abde-4ca5-abfc-4b7c5ac8b03b
Kutnenko, O.
77a1d8ad-6392-424c-90f7-e8836bb5cbc7
Borisova, I.
fd1320cf-9b38-4c66-8685-105059c29569
Okun, O.
10ebb8b0-d8df-4334-9321-1c88c284fa05
Zagoruiko, N.
2540f602-9f8b-41e7-9785-28ea207fdbd8
Alves, A.
87b9179e-abde-4ca5-abfc-4b7c5ac8b03b
Kutnenko, O.
77a1d8ad-6392-424c-90f7-e8836bb5cbc7
Borisova, I.
fd1320cf-9b38-4c66-8685-105059c29569

Okun, O., Zagoruiko, N., Alves, A., Kutnenko, O. and Borisova, I. (2006) Selection of more than one gene at a time for cancer prediction from gene expression data. In ESANN 2006 Proceedings - European Symposium on Artificial Neural Networks. pp. 551-556 .

Record type: Conference or Workshop Item (Paper)

Abstract

A new gene selection method capable of selecting more than one gene at a time is introduced. This characteristic contrasts it with almost all known methods assuming that there are no interactions between genes. The only exception is the pairwise gene selection method recently proposed by Bø and Jonassen [3]. Motivated by this method, we compare it and ours. Classification into healthy tissue and cancerous tumour is studied, where gene selection finds gene subsets well suitable for discriminating between these two classes. © 2006 i6doc.com publication. All rights reserved.

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Published date: 26 April 2006

Identifiers

Local EPrints ID: 494378
URI: http://eprints.soton.ac.uk/id/eprint/494378
PURE UUID: d203d011-7537-4bca-8d15-f68fce388be2
ORCID for A. Alves: ORCID iD orcid.org/0000-0001-8519-7356

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Date deposited: 07 Oct 2024 16:46
Last modified: 08 Oct 2024 02:13

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Contributors

Author: O. Okun
Author: N. Zagoruiko
Author: A. Alves ORCID iD
Author: O. Kutnenko
Author: I. Borisova

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