Computer Science Faculty Publications

Title

Text Analysis of MEDLINE for Discovering Functional Relationships among Genes: Evaluation of Keyword Extraction Weighting Schemes

Document Type

Article

Abstract

One of the key challenges of microarray studies is to derive biological insights from the gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the functional links among genes. However, the quality of the keyword lists significantly affects the clustering results. We compared two keyword weighting schemes: normalised z-score and term frequency-inverse document frequency (TFIDF). Two gene sets were tested to evaluate the effectiveness of the weighting schemes for keyword extraction for gene clustering. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords outperformed those produced from normalised z-score weighted keywords. The optimised algorithms should be useful for partitioning genes from microarray lists into functionally discrete clusters.

Publication Date

2006

Publication Title

International Journal of Data Mining and Bioinformatics

Volume

1

Issue

1

Start Page No.

88

End Page No.

110

ISSN

1748-5673

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