Scoring and summarising gene product clusters using the Gene Ontology
Scoring and summarising gene product clusters using the Gene Ontology
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DOI：
10.1504/ijdmb.2008.020523
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发表时间：
2008-09
影响因子：
0.3
通讯作者：
S. Denaxas;Christos Tjortjis
中科院分区：
文献类型：
--
作者：
S. Denaxas;Christos Tjortjis
We propose an approach for quantifying the biological relatedness between gene products, based on their properties, and measure their similarities using exclusively statistical NLP techniques and Gene Ontology (GO) annotations. We also present a novel similarity figure of merit, based on the vector space model, which assesses gene expression analysis results and scores gene product clusters' biological coherency, making sole use of their annotation terms and textual descriptions. We define query profiles which rapidly detect a gene product cluster's dominant biological properties. Experimental results validate our approach, and illustrate a strong correlation between our coherency score and gene expression patterns.
