The Goodman-Kruskal coefficient and its applications in genetic diagnosis of cancer

Author

Jaroszewicz, Szymon ; Simovici, Dan A. ; Kuo, Winston P. ; Ohno-Machado, Lucila

Author_Institution

Dept. of Comput. Sci., Univ. of Massachusetts, Boston, MA, USA

Volume

51

Issue

7

fYear

2004

fDate

7/1/2004 12:00:00 AM

Firstpage

1095

Lastpage

1102

Abstract

Increasing interest in new pattern recognition methods has been motivated by bioinformatics research. The analysis of gene expression data originated from microarrays constitutes an important application area for classification algorithms and illustrates the need for identifying important predictors. We show that the Goodman-Kruskal coefficient can be used for constructing minimal classifiers for tabular data, and we give an algorithm that can construct such classifiers.

Keywords

arrays; cancer; genetics; medical diagnostic computing; pattern classification; Goodman-Kruskal coefficient; bioinformatics; cancer; classification algorithms; gene expression; genetic diagnosis; microarrays; pattern recognition; predictors; Bioinformatics; Biological tissues; Cancer; Cells (biology); Computer science; DNA; Gene expression; Genetics; Glass; Pattern recognition; Algorithms; Cluster Analysis; Diagnosis, Computer-Assisted; Genetic Screening; Humans; Neoplasms; Oligonucleotide Array Sequence Analysis; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;

fLanguage

English

Journal_Title

Biomedical Engineering, IEEE Transactions on

Publisher

ieee

ISSN

0018-9294

Type

jour

DOI

10.1109/TBME.2004.827267

Filename

1306562