Bayesian ontology querying for accurate and noise-tolerant semantic searches

被引：44

作者：

Bauer, Sebastian ^{[1
]}

Koehler, Sebastian ^{[1
,2
]}

Schulz, Marcel H. ^{[3
,4
]}

Robinson, Peter N. ^{[1
,2
,3
]}

机构：

[1] Charite, Inst Med Genet & Human Genet, D-13353 Berlin, Germany

[2] Charite, Berlin Brandenburg Ctr Regenerat Therapies, D-13353 Berlin, Germany

[3] Max Planck Inst Mol Genet, D-14195 Berlin, Germany

[4] Carnegie Mellon Univ, Ray & Stephanie Lane Ctr Computat Biol, Pittsburgh, PA 15213 USA

来源：

BIOINFORMATICS | 2012年 / 28卷 / 19期

关键词：

GENE-ONTOLOGY; MODEL; TOOL;

D O I：

10.1093/bioinformatics/bts471

中图分类号：

Q5 [生物化学];

学科分类号：

070307 [化学生物学];

摘要：

Motivation: Ontologies provide a structured representation of the concepts of a domain of knowledge as well as the relations between them. Attribute ontologies are used to describe the characteristics of the items of a domain, such as the functions of proteins or the signs and symptoms of disease, which opens the possibility of searching a database of items for the best match to a list of observed or desired attributes. However, naive search methods do not perform well on realistic data because of noise in the data, imprecision in typical queries and because individual items may not display all attributes of the category they belong to. Results:: We present a method for combining ontological analysis with Bayesian networks to deal with noise, imprecision and attribute frequencies and demonstrate an application of our method as a differential diagnostic support system for human genetics.

引用

页码：2502 / 2508

页数：7

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