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EnglishRecently, a great effort in microarray data analysis is directed towards the study of the so-called gene sets. A gene set is defined by genes that are, somehow, functionally related. For example, genes appearing in a known biological pathway naturally define a gene set. The gene sets are usually identified from a priori biological knowledge. Nowadays, many bioinformatics resources store such kind of knowledge (see, for example, the Kyoto Encyclopedia of Genes and Genomes, among others). In this paper we exploit a multivariate approach, based on graphical models, to deal with gene sets defined by pathways. Given a sample of microarray data corresponding to two experimental conditions and a pathway linking some of the genes, we investigate whether the strength of the relations induced by the functional links change among the two experimental conditions.
| Titolo: | A graphical models approach for comparing gene sets | |
| Autore/i: | MASSA M.S; CHIOGNA M.; ROMUALDI C | |
| Autore/i Unibo: | ||
| Anno: | 2010 | |
| Titolo del libro: | Complex data modeling and computationally intensive statistical methods | |
| Pagina iniziale: | 115 | |
| Pagina finale: | 122 | |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1007/978-88-470-1386-5 | |
| Abstract: | Recently, a great effort in microarray data analysis is directed towards the study of the so-called gene sets. A gene set is defined by genes that are, somehow, functionally related. For example, genes appearing in a known biological pathway naturally define a gene set. The gene sets are usually identified from a priori biological knowledge. Nowadays, many bioinformatics resources store such kind of knowledge (see, for example, the Kyoto Encyclopedia of Genes and Genomes, among others). In this paper we exploit a multivariate approach, based on graphical models, to deal with gene sets defined by pathways. Given a sample of microarray data corresponding to two experimental conditions and a pathway linking some of the genes, we investigate whether the strength of the relations induced by the functional links change among the two experimental conditions. | |
| Data stato definitivo: | 13-nov-2018 | |
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