A comprehensive fuzzy-based framework for cancer microarray data gene expression analysis

Zhenyu Wang; Vasile Palade

doi:10.1109/BIBE.2007.4375680

A comprehensive fuzzy-based framework for cancer microarray data gene expression analysis

Zhenyu Wang, Vasile Palade

University of Oxford

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

20 Citations (Scopus)

Abstract

In this paper, we employ fuzzy techniques for analysing cancer microarray gene expression data. A fuzzy-based ensemble model and a comprehensive fuzzy-based framework for cancer microarray data analysis are being proposed. Our methods were tested on three benchmark microarray cancer data sets, namely Leukemia Cancer Data Set, Colon Cancer Data Set and Lymphoma Cancer Data Set. Comparing to other traditional statistical and machine learning models, the new approach can efficiently tackle several key problems in cancer microarray gene expression data analysis, including highly correlated genes, high dimensionality, highly noisy data and further explanation of the diagnosis results.

Original language	English
Title of host publication	Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Publisher	IEEE
Pages	1003-1010
Number of pages	8
ISBN (Print)	1424415098, 9781424415090
DOIs	https://doi.org/10.1109/BIBE.2007.4375680
Publication status	Published - 2007
Externally published	Yes
Event	7th IEEE International Conference on Bioinformatics and Bioengineering - Boston, United States Duration: 14 Jan 2007 → 17 Jan 2007

Conference

Conference	7th IEEE International Conference on Bioinformatics and Bioengineering
Abbreviated title	BIBE
Country/Territory	United States
City	Boston
Period	14/01/07 → 17/01/07

ASJC Scopus subject areas

Biotechnology
Genetics
Bioengineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/BIBE.2007.4375680

Cite this

Wang, Z & Palade, V 2007, A comprehensive fuzzy-based framework for cancer microarray data gene expression analysis. in Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE., 4375680, IEEE, pp. 1003-1010, 7th IEEE International Conference on Bioinformatics and Bioengineering, Boston, Massachusetts, United States, 14/01/07. https://doi.org/10.1109/BIBE.2007.4375680

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doi = "10.1109/BIBE.2007.4375680",

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AB - In this paper, we employ fuzzy techniques for analysing cancer microarray gene expression data. A fuzzy-based ensemble model and a comprehensive fuzzy-based framework for cancer microarray data analysis are being proposed. Our methods were tested on three benchmark microarray cancer data sets, namely Leukemia Cancer Data Set, Colon Cancer Data Set and Lymphoma Cancer Data Set. Comparing to other traditional statistical and machine learning models, the new approach can efficiently tackle several key problems in cancer microarray gene expression data analysis, including highly correlated genes, high dimensionality, highly noisy data and further explanation of the diagnosis results.

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ER -

A comprehensive fuzzy-based framework for cancer microarray data gene expression analysis

Abstract

Conference

ASJC Scopus subject areas

UN SDGs

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