<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>In this paper we present a method for evaluating the importance of GO terms which compose multi-attribute rules. The rules are generated for the purpose of biological interpretation of gene groups. Each multi-attribute rule is a combination of GO terms and, based on relationships among them, one can obtain a functional description of gene groups. We present a method which allows evaluating the influence of a given GO term on the quality of a rule and the quality of a whole set of rules. For each GO term, we compute how big its influence on the quality of generated set of rules and therefore the quality of the obtained description is. Based on the computed quality of GO terms, we propose a new algorithm of rule induction in order to obtain a more synthetic and more accurate description of gene groups than the description obtained by initially determined rules. The obtained GO terms ranking and newly obtained rules provide additional information about the biological function of genes that compose the analyzed group of genes.</p></abstract>

In this paper we present a method for evaluating the importance of GO terms which compose multi-attribute rules. The rules are generated for the purpose of biological interpretation of gene groups. Each multi-attribute rule is a combination of GO terms and, based on relationships among them, one can obtain a functional description of gene groups. We present a method which allows evaluating the influence of a given GO term on the quality of a rule and the quality of a whole set of rules. For each GO term, we compute how big its influence on the quality of generated set of rules and therefore the quality of the obtained description is. Based on the computed quality of GO terms, we propose a new algorithm of rule induction in order to obtain a more synthetic and more accurate description of gene groups than the description obtained by initially determined rules. The obtained GO terms ranking and newly obtained rules provide additional information about the biological function of genes that compose the analyzed group of genes.

Quality improvement of rule-based gene group descriptions using information about GO terms importance occurring in premises of determined rules

Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland

Institute of Innovative Technologies EMAG, Leopolda 31, 40-189 Katowice, Poland

International Journal of Applied Mathematics and Computer Science

In this paper we present a method for evaluating the importance of GO terms which compose multi-attribute rules. The rules are generated for the purpose of...

Quality improvement of rule-based gene group descriptions using information about GO terms importance occurring in premises of determined rules

Publié en ligne: 27 sept. 2010

Pages: 555 - 570

DOI: https://doi.org/10.2478/v10006-010-0041-3

Mots clés
decision rules, importance of rules premises, measures of rules interestingness, gene ontology, descriptions of gene groups

This content is open access.

Quality improvement of rule-based gene group descriptions using information about GO terms importance occurring in premises of determined rules

Publié en ligne: 27 sept. 2010

Pages: 555 - 570

DOI: https://doi.org/10.2478/v10006-010-0041-3

Mots clésdecision rules, importance of rules premises, measures of rules interestingness, gene ontology, descriptions of gene groups

This content is open access.

Mots clés
decision rules, importance of rules premises, measures of rules interestingness, gene ontology, descriptions of gene groups