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Information Content-Based Gene Ontology Semantic Similarity Approaches: Toward a Unified Framework Theory
Joint Authors
Mazandu, Gaston K.
Mulder, Nicola J.
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-09-02
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Several approaches have been proposed for computing term information content (IC) and semantic similarity scores within the gene ontology (GO) directed acyclic graph (DAG).
These approaches contributed to improving protein analyses at the functional level.
Considering the recent proliferation of these approaches, a unified theory in a well-defined mathematical framework is necessary in order to provide a theoretical basis for validating these approaches.
We review the existing IC-based ontological similarity approaches developed in the context of biomedical and bioinformatics fields to propose a general framework and unified description of all these measures.
We have conducted an experimental evaluation to assess the impact of IC approaches, different normalization models, and correction factors on the performance of a functional similarity metric.
Results reveal that considering only parents or only children of terms when assessing information content or semantic similarity scores negatively impacts the approach under consideration.
This study produces a unified framework for current and future GO semantic similarity measures and provides theoretical basics for comparing different approaches.
The experimental evaluation of different approaches based on different term information content models paves the way towards a solution to the issue of scoring a term’s specificity in the GO DAG.
American Psychological Association (APA)
Mazandu, Gaston K.& Mulder, Nicola J.. 2013. Information Content-Based Gene Ontology Semantic Similarity Approaches: Toward a Unified Framework Theory. BioMed Research International،Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-1003915
Modern Language Association (MLA)
Mazandu, Gaston K.& Mulder, Nicola J.. Information Content-Based Gene Ontology Semantic Similarity Approaches: Toward a Unified Framework Theory. BioMed Research International No. 2013 (2013), pp.1-11.
https://search.emarefa.net/detail/BIM-1003915
American Medical Association (AMA)
Mazandu, Gaston K.& Mulder, Nicola J.. Information Content-Based Gene Ontology Semantic Similarity Approaches: Toward a Unified Framework Theory. BioMed Research International. 2013. Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-1003915
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1003915