Using Enriched Ontology Structure for Improving Statistical Models of Gene Annotation Sets

Autor:	Frank Rügheimer
Rok vydání:	2010
Předmět:	Structure (mathematical logic) Interpretation (logic) Computer science Gene ontology media_common.quotation_subject Statistical model Gene Annotation Ontology (information science) computer.software_genre Probability distribution Quality (business) Data mining computer media_common
Zdroj:	Communications in Computer and Information Science ISBN: 9783642140570 IPMU (2)
DOI:	10.1007/978-3-642-14058-7_6
Popis:	The statistical analysis of annotations provided for genes and gene products supports biologists in their interpretation of data from large-scale experiments. Comparing, for instance, distributions of annotations associated with differentially expressed genes to a reference, highlights interesting observations and permits to formulate hypotheses about changes to the activity pathways and their interaction under the chosen experimental conditions. The ability to reliably and efficiently detect relevant changes depends on properties of the chosen distribution models. This paper compares four methods to represent statistical information about gene annotations and compares their performance on a public dataset with respect to a number of evaluation measures. The evaluation results demonstrate that the inclusion of structure information from the Gene Ontology enhances overall approximation quality by providing suitable decompositions of probability distributions.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::9846274139d4bd2e676a2e455cc553a2 https://doi.org/10.1007/978-3-642-14058-7_6 Zobrazit plný text záznamu