Abstract
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.
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Dessì, N., Dessì, S., Pascariello, E., Pes, B. (2015). Exploring the Relatedness of Gene Sets. In: DI Serio, C., Liò, P., Nonis, A., Tagliaferri, R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2014. Lecture Notes in Computer Science(), vol 8623. Springer, Cham. https://doi.org/10.1007/978-3-319-24462-4_4
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DOI: https://doi.org/10.1007/978-3-319-24462-4_4
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