NDLI: Using semantic similarity to detect features in yeast protein complexes

Content Provider	IEEE Xplore Digital Library
Author	Guzzi, P.H. Milano, M. Veltri, P. Cannataro, M.
Copyright Year	2011
Description	Author affiliation: University of Catanzaro, Italy (Guzzi, P.H.; Milano, M.; Veltri, P.; Cannataro, M.)
Abstract	Biological data stored in databases can be associated with information (knowledge) such as experiments, properties and functions, response to drugs etc. Such a knowledge is often stored in biological ontologies. Gene Ontology is one of the main resource of biological knowledge providing both a categorization of terms and a source of annotation for genes and proteins. This enables the use of ontology-based methodologies for the analysis of proteins and their functions. One methodology is based on semantic based similarity measures. Recently there is a growing interest in the use of semantic based methodologies to the analysis of protein interaction data such as the prediction of protein complexes based on semantic similarity measures. Despite this interest, there is the need for an assessment of semantic measures as well as a deep study on the impact of the chosen measure in the obtained results. This paper treats the problem of using semantic similarity measure to analyse protein complexes and to improve protein complexes prediction frameworks. Tests have been performed in yeast protein complexes. Results indicate that there exists a bias among measures as well as an higher value of semantic similarity within proteins that participate in the same complex, proving both a possible use of semantic similarity protein complexes prediction and a suggestion in the measure.
Starting Page	495
Ending Page	502
File Size	936939
Page Count	8
File Format	PDF
ISBN	9781457716126
e-ISBN	9781457716133
DOI	10.1109/BIBMW.2011.6112419
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Proteins Weight measurement Ontologies Semantic Similarity Measures Protein engineering Protein Interaction Networks Databases Semantics Ontologies Particle measurements
Content Type	Text
Resource Type	Article

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