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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Exploring the Relatedness of Gene Sets
verfasst von : Nicoletta Dessì, Stefania Dessì, Emanuele Pascariello, Barbara Pes
Erschienen in: Computational Intelligence Methods for Bioinformatics and Biostatistics
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A key activity for life scientists is the exploration of the relatedness of a set of genes in order to differentiate genes performing coherently related functions from random grouped genes. This paper considers exploring the relatedness within two popular bio-organizations, namely gene families and pathways. This exploration is carried out by integrating different resources (ontologies, texts, expert classifications) and aims to suggest patterns that facilitate the biologists in obtaining a more comprehensive vision of differences in gene behaviour. Our approach is based on the annotation of a specialized corpus of texts (the gene summaries) that condense the description of functions/processes in which genes are involved. By annotating these summaries with different ontologies a set of descriptor terms is derived and compared in order to obtain a measure of relatedness within the bio-organizations we considered. Finally, the most important annotations within each family are extracted using a text categorization method.