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Identifying Candidate Disease Gene GAD2 for Obesity by Computational Gene Prioritization Tool ENDEAVOUR

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Bio-Science and Bio-Technology (BSBT 2009)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 57))

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Abstract

Identifying potential disease genes for complex disease is very important for understanding disease pathogenesis and providing preventive measures. The computational gene prioritization tools provide a promising and effective way for disease gene identification. Gene GAD2 on Chromosome 10p12 is a disputing candidate disease gene for obesity because of the contradictory conclusions obtained by association studies of different researchers. In this paper, a computational tool ENDEAVOUR is used to verify the probability of gene GAD2 being an obesity candidate disease gene. ENDEAVOUR evaluates each candidate gene based on its similarity with the training genes (known disease genes). The high prioritization of gene GAD2 in the computational results means that the gene GAD2 has high probability to be a disease gene for obesity.

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Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Huanping Zhang, Xiaofeng Song & Huinan Wang

Authors
  1. Huanping Zhang
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  2. Xiaofeng Song
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  3. Huinan Wang
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Editor information

Editors and Affiliations

  1. Infobright Inc., M5E 1P8, Toronto, ON, Canada

    Dominik Ślęzak

  2. Chair of Integrated Electronic Systems, School of Engineering and Electronics, University of Edinburgh, The King’s Buildings, Mayfield Road, EH9 3JL, Edinburgh, UK

    Tughrul Arslan

  3. National Chiao Tung University, Hsinchu, Taiwan

    Wai-Chi Fang

  4. Shanghai University, Shanghai, China

    Xiaofeng Song

  5. Hannam University, 306-791, Daejeon, South Korea

    Tai-hoon Kim

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© 2009 Springer-Verlag Berlin Heidelberg

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Zhang, H., Song, X., Wang, H. (2009). Identifying Candidate Disease Gene GAD2 for Obesity by Computational Gene Prioritization Tool ENDEAVOUR. In: Ślęzak, D., Arslan, T., Fang, WC., Song, X., Kim, Th. (eds) Bio-Science and Bio-Technology. BSBT 2009. Communications in Computer and Information Science, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10616-3_2

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  • DOI: https://doi.org/10.1007/978-3-642-10616-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10615-6

  • Online ISBN: 978-3-642-10616-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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