Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/12267
Title: Integrative biological network analysis to identify shared genes in metabolic disorders
Authors: Tenekeci, Samet
Işık, Zerrin
01. Izmir Institute of Technology
Dokuz Eylül Üniversitesi
Keywords: Coronary artery disease
Gene expression
Gene ontology
Metabolic syndrome
Issue Date: 2022
Publisher: Institute of Electrical and Electronics Engineers
Abstract: Identification of common molecular mechanisms in interrelated diseases is essential for better prognoses and targeted therapies. However, complexity of metabolic pathways makes it difficult to discover common disease genes underlying metabolic disorders; and it requires more sophisticated bioinformatics models that combine different types of biological data and computational methods. Accordingly, we built an integrative network analysis model to identify shared disease genes in metabolic syndrome (MS), type 2 diabetes (T2D), and coronary artery disease (CAD). We constructed weighted gene co-expression networks by combining gene expression, protein-protein interaction, and gene ontology data from multiple sources. For 90 different configurations of disease networks, we detected the significant modules by using MCL, SPICi, and Linkcomm graph clustering algorithms. We also performed a comparative evaluation on disease modules to determine the best method providing the highest biological validity. By overlapping the disease modules, we identified 22 shared genes for MS-CAD and T2D-CAD. Moreover, 19 out of these genes were directly or indirectly associated with relevant diseases in the previous medical studies. This study does not only demonstrate the performance of different biological data sources and computational methods in disease-gene discovery, but also offers potential insights into common genetic mechanisms of the metabolic disorders.
URI: https://doi.org/10.1109/TCBB.2020.2993301
https://hdl.handle.net/11147/12267
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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