Mining association rules from gene ontology and protein networks: Promises and challenges

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Abstract

In biology, the accumulation of raw experimental data has been accompanied by the accumulation of functional information encoded by using annotation terms. Such annotations are organized into ontologies such as Gene Ontology. Each annotation may be derived using different methods that yield to different reliability of such information. The analysis of this annotated data using association rules may evidence the co-occurrence of annotations improving for instance annotation quality. Here we give a short survey of these methods discussing possible future directions of research. We considered in particular the impact of the nature of annotations on algorithms performances by discussing two case studies and evidencing the impact of quality of annotations. © The Authors. Published by Elsevier B.V.

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APA

Guzzi, P. H., Milano, M., & Cannataro, M. (2014). Mining association rules from gene ontology and protein networks: Promises and challenges. In Procedia Computer Science (Vol. 29, pp. 1970–1980). Elsevier. https://doi.org/10.1016/j.procs.2014.05.181

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