Abstract
The article presents and analyses three graph processing issues that can be identified in three methods of GO term similarity evaluation. The solutions of these problems are implemented in Neo4j graph database environment. Each of the issues can be solved directly by a single Cypher query or can be divided into several queries which results have to be merged. The comparison of the introduced solutions is presented in terms of time and memory effectivness. The results show how to implement the effective solutions of this class of issues.
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© 2014 Springer International Publishing Switzerland
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Stypka, Ł., Kozielski, M. (2014). Methods of Gene Ontology Term Similarity Analysis in Graph Database Environment. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures, and Structures. BDAS 2014. Communications in Computer and Information Science, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-06932-6_33
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DOI: https://doi.org/10.1007/978-3-319-06932-6_33
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06931-9
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