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A Review: Biological Insights on Knowledge Graphs

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New Trends in Database and Information Systems (ADBIS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1652))

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Abstract

Knowledge graphs in the biomedical context are spreading rapidly attracting the strong interest of the research due to their natural way of representing biomedical knowledge by integrating heterogeneous domains (genomic, pharmaceutical, clinical etc.). In this paper we will give an overview of the application of knowledge graphs from the biological to the clinical context and show the most recent ways of representing biomedical knowledge with embeddings (KGE). Finally, we present challenges, such as the integration of different knowledge graphs and the interpretability of predictions of new relations, that recent improvements in this field face. Furthermore, we introduce promising future avenues of research (e.g. the use of multimodal approaches and Simplicial neural networks) in the biomedical field and precision medicine.

Y. Galluzzo—Now working at Expleo Italia S.p.a.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Palerme, Palerme, Italy

    Ylenia Galluzzo

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  1. Ylenia Galluzzo
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Correspondence to Ylenia Galluzzo .

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Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Silvia Chiusano

  2. Politecnico di Torino, Turin, Italy

    Tania Cerquitelli

  3. Poznań University of Technology, Poznań, Poland

    Robert Wrembel

  4. Norwegian University of Science and Technology, Trondheim, Norway

    Kjetil Nørvåg

  5. University of Genoa, Genoa, Italy

    Barbara Catania

  6. CNRS, Villeurbanne Cedex, France

    Genoveva Vargas-Solar

  7. University of Calabria, Rende, Italy

    Ester Zumpano

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Galluzzo, Y. (2022). A Review: Biological Insights on Knowledge Graphs. In: Chiusano, S., et al. New Trends in Database and Information Systems. ADBIS 2022. Communications in Computer and Information Science, vol 1652. Springer, Cham. https://doi.org/10.1007/978-3-031-15743-1_36

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  • DOI: https://doi.org/10.1007/978-3-031-15743-1_36

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