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Annotation and retrieval in protein interaction databases

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Abstract

Biological databases have been developed with a special focus on the efficient retrieval of single records or the efficient computation of specialized bioinformatics algorithms against the overall database, such as in sequence alignment. The continuos production of biological knowledge spread on several biological databases and ontologies, such as Gene Ontology, and the availability of efficient techniques to handle such knowledge, such as annotation and semantic similarity measures, enable the development on novel bioinformatics applications that explicitly use and integrate such knowledge. After introducing the annotation process and the main semantic similarity measures, this paper shows how annotations and semantic similarity can be exploited to improve the extraction and analysis of biologically relevant data from protein interaction databases. As case studies, the paper presents two novel software tools, OntoPIN and CytoSeVis, both based on the use of Gene Ontology annotations, for the advanced querying of protein interaction databases and for the enhanced visualization of protein interaction networks.

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Authors and Affiliations

  1. Department of Medical and Surgical Sciences, Magna Graecia University of Catanzaro, 88100, Catanzaro, Italy

    Mario Cannataro, Pietro Hiram Guzzi & Pierangelo Veltri

Authors
  1. Mario Cannataro
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  2. Pietro Hiram Guzzi
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  3. Pierangelo Veltri
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Correspondence to Mario Cannataro.

Additional information

Contribution to the Focus Point on “Pattern Recognition Tools for Proteomics” edited by V. Cantoni.

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Cannataro, M., Hiram Guzzi, P. & Veltri, P. Annotation and retrieval in protein interaction databases. Eur. Phys. J. Plus 129, 135 (2014). https://doi.org/10.1140/epjp/i2014-14135-x

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