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International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics

CIBB 2016: Computational Intelligence Methods for Bioinformatics and Biostatistics pp 235–247Cite as

Semantic Clustering for Identifying Overlapping Biological Communities

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10477))

Abstract

Proteins encoded by the genes associated with a common disorder interact together, participate in similar pathways, and share Gene Ontology (GO) terms. Drug discovery for certain disease may arise from a hypothesis that genes contributing to a common disorder have an increased tendency for their products to be linked at various functional levels. This may be induced from experimental studies of protein-protein interactions, co-regulation, co-expression, and annotated semantic information (e.g., those stored in Gene Ontology). Our aim is to improve the quality of aggregation discovery in dense biological interactions by incorporating such information embedded in biological repositories and mapping them in the spectral embedding space.

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Notes

  1. 1.

    http://www.genome.jp/kegg/.

  2. 2.

    http://www.uniprot.org/.

  3. 3.

    http://www.lasige.di.fc.ul.pt/webtools/proteinon/.

  4. 4.

    http://www.cbio.uct.ac.za/ITGOM/tools/itgom.php.

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Authors and Affiliations

  1. DIBRIS - Dip. di Informatica, Bioingegneria, Robotica e Ingegneria dei Sistemi Università di Genova, Via Dodecaneso 35, 16146, Genova, Italy

    Hassan Mahmoud, Francesco Masulli & Stefano Rovetta

  2. Faculty of Computer Science, Benha University, Benha, Egypt

    Hassan Mahmoud

  3. Sbarro Institute for Cancer Research and Molecular Medicine College of Science and Technology, Temple University, Philadelphia, PA, USA

    Francesco Masulli

Authors
  1. Hassan Mahmoud
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  2. Francesco Masulli
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  3. Stefano Rovetta
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Correspondence to Hassan Mahmoud .

Editor information

Editors and Affiliations

  1. Computing Science and Mathematics, University of Stirling, Stirling, United Kingdom

    Andrea Bracciali

  2. School of Informatics, University of Edinburgh, Edinburgh, United Kingdom

    Giulio Caravagna

  3. Department of Computer Science, Brunel University London, Uxbridge, Middlesex, United Kingdom

    David Gilbert

  4. Department of Management and Innovation Systems DISA-MIS, University of Salerno, Fisciano, Italy

    Roberto Tagliaferri

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Mahmoud, H., Masulli, F., Rovetta, S. (2017). Semantic Clustering for Identifying Overlapping Biological Communities. In: Bracciali, A., Caravagna, G., Gilbert, D., Tagliaferri, R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. Lecture Notes in Computer Science(), vol 10477. Springer, Cham. https://doi.org/10.1007/978-3-319-67834-4_19

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  • DOI: https://doi.org/10.1007/978-3-319-67834-4_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67833-7

  • Online ISBN: 978-3-319-67834-4

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