@inproceedings{6234cdf392c7485089629b1a5d5a379e,
title = "Evaluation of semantic term and gene similarity measures",
abstract = "In this paper we present the results of the research verifying how the functional description of genes contained in Gene Ontology database is related to genes expression values recorded during biological experiments. We compare several different gene similarity measures and semantic term similarity measures, and evaluate how the similarity of genes based on Gene Ontology terms is correlated with similarity of genes based on expression profiles. The analysis are preformed on three different datasets and we show that there is no single term similarity measure that always gives the best correlation results. The choice of the best term similarity measure depends on dataset characteristic.",
keywords = "Gene Ontology database, experssion analysis, genes similarity, semantic term similarity",
author = "Michal Kozielski and Aleksandra Gruca",
year = "2011",
doi = "10.1007/978-3-642-21786-9\_66",
language = "English",
isbn = "9783642217852",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "406--411",
booktitle = "Pattern Recognition and Machine Intelligence - 4th International Conference, PReMI 2011, Proceedings",
note = "4th International Conference on Pattern Recognition and Machine Intelligence, PReMI-2011 ; Conference date: 27-06-2011 Through 01-07-2011",
}