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NETME: On-the-Fly Knowledge Network Construction from Biomedical Literature

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Complex Networks & Their Applications IX (COMPLEX NETWORKS 2020 2020)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 944))

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Abstract

The huge amount of biological literature, which daily increases, represents a strategic resource to automatically extract and gain knowledge concerning relations among biological elements. Knowledge Networks are helpful tools in the context of biological knowledge discovery and modeling. Here we introduce a novel system called NETME, which, starting from a set of fulltext obtained from PubMed, through an easy-to-use web interface, interactively extracts a group of biological elements stored into a selected list of ontological databases and then synthesizes a network with inferred relations among such elements. The results clearly show that our tool is capable to efficiently and efficaciously infer reliable functional biological networks.

A. Muscolino and A. Di Maria—Equal contributor.

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Author information

Authors and Affiliations

  1. Department of Physics and Astronomy, University of Catania, Catania, Italy

    Alessandro Muscolino & Antonio Di Maria

  2. Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy

    Salvatore Alaimo, Alfredo Ferro & Alfredo Pulvirenti

  3. Department of Maths and Computer Science, University of Catania, Catania, Italy

    Stefano Borzì

  4. Department Computer Science, University of Pisa, Pisa, Italy

    Paolo Ferragina

Authors
  1. Alessandro Muscolino
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  2. Antonio Di Maria
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  3. Salvatore Alaimo
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  4. Stefano Borzì
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  5. Paolo Ferragina
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  6. Alfredo Ferro
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  7. Alfredo Pulvirenti
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Corresponding author

Correspondence to Alfredo Pulvirenti .

Editor information

Editors and Affiliations

  1. Grupo de Sistemas Complejos, Universidad Politécnica de Madrid, Madrid, Madrid, Spain

    Rosa M. Benito

  2. IUT Lumière, University of Lyon, Bron Cedex, France

    Chantal Cherifi

  3. LE2I, UFR Sciences et Techniques, Université de Bourgogne, Dijon, France

    Hocine Cherifi

  4. Grupo Interdisciplinar de Sistemas Complejos, Departamento de Matematicas, Universidad Carlos III de Madrid, Leganés, Madrid, Spain

    Esteban Moro

  5. Center for Social and Biomedical Complexity, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA

    Luis Mateus Rocha

  6. Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Tarragona, Spain

    Marta Sales-Pardo

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Muscolino, A. et al. (2021). NETME: On-the-Fly Knowledge Network Construction from Biomedical Literature. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications IX. COMPLEX NETWORKS 2020 2020. Studies in Computational Intelligence, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-65351-4_31

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  • DOI: https://doi.org/10.1007/978-3-030-65351-4_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65350-7

  • Online ISBN: 978-3-030-65351-4

  • eBook Packages: EngineeringEngineering (R0)

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