Exploring the relatedness of gene sets

DESSI, NICOLETTA;DESSI', STEFANIA;PES, BARBARA
2015-01-01

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.
2015
Inglese
Computational intelligence methods for bioinformatics and biostatistics
9783319244617
Springer
Clelia DI Serio, Pietro Liò, Alessandro Nonis, Roberto Tagliaferri
8623
44
56
13
http://link.springer.com/chapter/10.1007%2F978-3-319-24462-4_4
11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2014
Contributo
Esperti anonimi
2014
Cambridge, UK
internazionale
scientifica
Gene relatedness; Ontology annotation; Semantic similarity; Text mining
no
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Dessi, Nicoletta; Dessi', Stefania; Pascariello, Emanuele; Pes, Barbara
273
4
4.1 Contributo in Atti di convegno
reserved
info:eu-repo/semantics/conferencePaper
File in questo prodotto:
File Dimensione Formato  
CIBB2014_post.pdf

Solo gestori archivio

Descrizione: Articolo principale
Tipologia: versione editoriale
Dimensione 399.84 kB
Formato Adobe PDF
399.84 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Questionario e social

Condividi su:
Impostazioni cookie