Protein Function Prediction Using Semantic Similarity Metrics and Random Walk Algorithm

Ivanoska, Ilinka and Trivodaliev, Kire and Kalajdziski, Slobodan (2012) Protein Function Prediction Using Semantic Similarity Metrics and Random Walk Algorithm. In: Proceedings of the Nineth Conference on Informatics and Information Technology. Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia, Skopje, Macedonia, pp. 105-109. ISBN 978-608-4699-01-9

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Abstract

Most protein function prediction methods that have been proposed, are based on sequence or structure protein similarity and do not take into consideration the semantic similarity extracted from protein knowledge databases such as Gene Ontology. In this paper we present an approach for protein function prediction using semantic similarity metrics and the whole network topology of a protein interaction network by using a "semantic driven" random walk with restart. Different semantic similarity metrics are explored and future results should show the relevance of different semantic similarity metrics on protein function prediction using random walk with restart. To achieve the final goal of protein function prediction, the best semantic similarity metric should be used.

Item Type: Book Section
Subjects: International Conference on Informatics and Information Technologies > Intelligent Systems
International Conference on Informatics and Information Technologies > Robotics
International Conference on Informatics and Information Technologies > Bioinformatics
Depositing User: Vangel Ajanovski
Date Deposited: 28 Oct 2016 00:15
Last Modified: 28 Oct 2016 00:15
URI: http://eprints.finki.ukim.mk/id/eprint/11129

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