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A Semantic Framework Supporting Multilayer Networks Analysis for Rare Diseases

Author

Listed:
  • Nicola Capuano

    (University of Basilicata, Italy)

  • Pasquale Foggia

    (University of Salerno, Italy)

  • Luca Greco

    (University of Salerno, Italy)

  • Pierluigi Ritrovato

    (University of Salerno, Italy)

Abstract

Understanding the role played by genetic variations in diseases, exploring genomic variants and discovering disease-associated loci are among the most pressing challenges of genomic medicine. A huge and ever-increasing amount of information is available to researchers to address these challenges. Unfortunately, it is stored in fragmented ontologies and databases, which use heterogeneous formats and poorly integrated schemas. To overcome these limitations, we propose a linked data approach, based on the formalism of multilayer networks, able to integrate and harmonize biomedical information from multiple sources into a single dense network covering different aspects on Neuroendocrine Neoplasms (NENs). The proposed integration schema consists of three interconnected layers representing, respectively, information on the disease, on the affected genes, on the related biological processes and molecular functions. An easy-to-use client-server application was also developed to browse and search for information on the model supporting multilayer network analysis.

Suggested Citation

  • Nicola Capuano & Pasquale Foggia & Luca Greco & Pierluigi Ritrovato, 2022. "A Semantic Framework Supporting Multilayer Networks Analysis for Rare Diseases," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 18(1), pages 1-22, January.
    • Handle: RePEc:igg:jswis0:v:18:y:2022:i:1:p:1-22
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    References listed on IDEAS

    as
    1. Said Fathalla, 2018. "Detecting Human Diseases Relatedness: A Spreading Activation Approach Over Ontologies," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 14(3), pages 120-133, July.
    2. Adebayo Adewumi Abayomi-Alli & Oluwasefunmi 'Tale Arogundade & Sanjay Misra & Mulkah Opeyemi Akala & Abiodun Motunrayo Ikotun & Bolanle Adefowoke Ojokoh, 2021. "An Ontology-Based Information Extraction System for Organic Farming," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 17(2), pages 79-99, April.
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    1. Kumari, Pooja & Shankar, Amit & Behl, Abhishek & Pereira, Vijay & Yahiaoui, Dorra & Laker, Benjamin & Gupta, Brij B. & Arya, Varsha, 2024. "Investigating the barriers towards adoption and implementation of open innovation in healthcare," Technological Forecasting and Social Change, Elsevier, vol. 200(C).

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