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International Conference on Intelligent and Interactive Systems and Applications

IISA 2018: Advances in Intelligent, Interactive Systems and Applications pp 109–114Cite as

An Improved Multi-factor Dimensionality Reduction Approach to Identify Gene-Gene Interactions

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 885))

Abstract

Genetic component of disease risk can be determined by gene–gene interactions. Multifactor dimensionality reduction (MDR) has widely used to identify gene–gene interactions based on the binary classification into high- or low-risk to evaluate the gene–gene interactions. However, the binary classification could not reflect the uncertainty of high- or low-risk classification. In this study, an improved classification method based on fuzzy sigmoid function was proposed to enhance MDR to identify GGIs. A total of 40 simulation data sets were used to compare the detection success rates of the improved MDR with the original MDR. The results expressed that our improved MDR obtained better detection success rates than MDR.

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Findings

This work was partly supported by the Ministry of Science and Technology in Taiwan (under Grant no. 105 – 2221 – E – 151 – 053 – MY2 and 106 – 2811 – E – 151 – 002 –.

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Authors and Affiliations

  1. Department of Chemical Engineering and Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan

    Li-Yeh Chuang

  2. Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan

    Yu-Da Lin & Cheng-Hong Yang

  3. Graduate Institute of Clinical Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan

    Cheng-Hong Yang

Authors
  1. Li-Yeh Chuang
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  2. Yu-Da Lin
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  3. Cheng-Hong Yang
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Corresponding authors

Correspondence to Yu-Da Lin or Cheng-Hong Yang .

Editor information

Editors and Affiliations

  1. Department de Ciències de la Computació, Universitat Politècnica de Catalunya, Barcelona, Spain

    Fatos Xhafa

  2. Department of Computer Science and Engineering, Faculty of Engineering and Technology, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  3. Department of Business Systems and Analytics, La Salle University, Philadelphia, PA, USA

    Madjid Tavana

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Chuang, LY., Lin, YD., Yang, CH. (2019). An Improved Multi-factor Dimensionality Reduction Approach to Identify Gene-Gene Interactions. In: Xhafa, F., Patnaik, S., Tavana, M. (eds) Advances in Intelligent, Interactive Systems and Applications. IISA 2018. Advances in Intelligent Systems and Computing, vol 885. Springer, Cham. https://doi.org/10.1007/978-3-030-02804-6_14

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