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Joint International Semantic Technology Conference

JIST 2018: Semantic Technology pp 410–417Cite as

Integrated Semantic Model for Complex Disease Network

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11341))

Abstract

To understand biological phenomena, biologists have identified the interactions between biological molecules in vivo. Until recently, all of the unique and interactive information of such molecules has been built into a database and made available online. Among them, there was an effort to understand the relationship of molecules based on biological pathways, and a standard model called BioPAX was made to enable interchange and operation of data. In particular, Pathway Commons integrates other biological data besides biological pathways using BioPAX. We are interested in identifying the molecular mechanisms of disease and recommending drugs for treatment. In addition to data provided by Pathway Commons, additional disease and drug data was added to be used in various analysis. We extended the model to express the data that BioPAX could not cover and converted all the data to RDF based on the model. We integrate and present diverse biological data using semantic technologies from the perspective of representing disease networks. We hope that this information will aid in a deeper understanding of disease and drug recommendations.

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Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and future Planning (No. NRF-2017R1A2B2008729).

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Authors and Affiliations

  1. Biomedical Knowledge Engineering Laboratory, Seoul National University, Seoul, Korea

    Junho Park, Sungkwon Yang & Hong-Gee Kim

Authors
  1. Junho Park
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  2. Sungkwon Yang
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  3. Hong-Gee Kim
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Corresponding author

Correspondence to Hong-Gee Kim .

Editor information

Editors and Affiliations

  1. National Institute of Informatics, Tokyo, Japan

    Ryutaro Ichise

  2. Accenture Labs, Dublin, Ireland

    Freddy Lecue

  3. Japan Science and Technology Agency, Tokyo, Japan

    Takahiro Kawamura

  4. Peking University, Beijing, China

    Dongyan Zhao

  5. Imperial College London, London, UK

    Stephen Muggleton

  6. Osaka University, Osaka, Japan

    Kouji Kozaki

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Park, J., Yang, S., Kim, HG. (2018). Integrated Semantic Model for Complex Disease Network. In: Ichise, R., Lecue, F., Kawamura, T., Zhao, D., Muggleton, S., Kozaki, K. (eds) Semantic Technology. JIST 2018. Lecture Notes in Computer Science(), vol 11341. Springer, Cham. https://doi.org/10.1007/978-3-030-04284-4_28

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  • DOI: https://doi.org/10.1007/978-3-030-04284-4_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04283-7

  • Online ISBN: 978-3-030-04284-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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