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Knowledge-Based Identification of Homogenous Structures in Gene Sets

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Information Systems and Technologies (WorldCIST 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 468))

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Abstract

The analysis of gene expression data plays a crucial role in disease diagnosis. However, such analysis is rather complex due to the high-dimensional gene space. This works shows that semantically related genes can be grouped using biological knowledge in the Gene Ontology (GO) database. The GO defines knowledge phrases called GO terms describing biological functions of genes. These knowledge phrases are typically used when discussing individual components of the ontologies. By exploiting the term frequency-inverse document frequency (tf-idf) as a distance measure between two genes, this distance is used in structure analysis on four gene sets causally associated with pain and the chronification of pain, hearing loss, cancer, and drug addiction. The analysis employs the Databionic swarm (DBS). The results show distinctive homogenous groups in each set of genes outperforming related work. This work outlines the successful application of information retrieval dissimilarity measure and structure analysis on gene sets using the knowledge base of the Gene Ontology. Furthermore, it enables in the future a separate analysis of gene subspaces.

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Author information

Authors and Affiliations

  1. Faculty of Mathematics and Computer Science, University of Marburg, Marburg, Germany

    Michael C. Thrun

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  1. Michael C. Thrun
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Correspondence to Michael C. Thrun .

Editor information

Editors and Affiliations

  1. ISEG, Universidade de Lisboa, Lisbon, Portugal

    Alvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda

  4. DCT, Universidade Portucalense, Porto, Portugal

    Fernando Moreira

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Thrun, M.C. (2022). Knowledge-Based Identification of Homogenous Structures in Gene Sets. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F. (eds) Information Systems and Technologies. WorldCIST 2022. Lecture Notes in Networks and Systems, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-04826-5_9

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