Comparison of the Data-based and Gene Ontology-Based Approaches to Cluster Validation Methods for Gene Microarrays

Author

Bolshakova, Nadia ; Zamolotskikh, Anton ; Cunningham, Pádraig

Author_Institution

Dept. of Comput. Sci., Trinity Coll., Dublin

fYear

0

fDate

0-0 0

Firstpage

539

Lastpage

543

Abstract

The paper presents a comparison of the data-based and gene ontology (GO)-based approaches to cluster validation methods for gene microarray analysis. We apply a homogeneous approach to obtaining metrics from different GO-based similarity measures and a normalization of validation index values, that allows us to compare them to each other as well as to data-based validation indices. The results show strong correlation between both GO-based and data-based validation indices. The results suggest that this may represent an effective tool to support biomedical knowledge discovery tasks based on gene expression data

Keywords

arrays; data mining; genetics; medical computing; molecular biophysics; ontologies (artificial intelligence); statistical analysis; biomedical knowledge discovery tasks; cluster validation methods; data-based validation indices; gene expression; gene microarrays; gene ontology-based validation indices; homogeneous approach; normalization; similarity measures; Biological information theory; Biomedical measurements; Clustering algorithms; Computer science; Databases; Gene expression; Ontologies; Pharmaceutical technology; Proteomics; Vocabulary;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer-Based Medical Systems, 2006. CBMS 2006. 19th IEEE International Symposium on

Conference_Location

Salt Lake City, UT

ISSN

1063-7125

Print_ISBN

0-7695-2517-1

Type

conf

DOI

10.1109/CBMS.2006.69

Filename

1647626