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Ranking of Cancer Mediating Genes: A Novel Approach Using Genetic Algorithm in DNA Microarray Gene Expression Dataset

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Advances in Computing and Data Sciences (ICACDS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 906))

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Abstract

Genes need to be investigated either in Gene Interaction Network or in a DNA microarray gene expression data to understand the role they play in complex diseases like cancer. The prioritized genes can help us to know the molecular mechanism, as well as to discover the promising candidates of cancer. Several gene ranking algorithms already have been proposed that produces the top ranked genes according to their importance with respect to a particular disease. In this work, we have developed one Genetic Algorithm (GA) based algorithm, MicroarrayGA, to rank the genes responsible for a particular cancer to occur. The whole research works on six datasets like Colorectal Cancer, Diffuse Large B-Cell Lymphoma, Pediatric Immune Thrombocytopenia (ITP), Small Cell Lung Cancer (SCLC), Breast Cancer and Prostate Cancer, publicly available from NCBI (National Center for Biotechnology Information) online repository. We have validated the outcome of the proposed algorithm by classification step using Support Vector Machine (SVM) classifier and we have also compared the results of MicroarrayGA with three existing methods on the basis of percentage of accuracy, precision, recall, F1-Score and G-Mean metrics.

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Author information

Authors and Affiliations

  1. Department of CSE, Heritage Institute of Technology, Kolkata, 700107, West Bengal, India

    Sujay Saha

  2. Department of CSE, National Institute of Technology Calicut, Kattangal, 673601, Kerala, India

    Priyojit Das

  3. Department of CSE, Netaji Subhash Engineering College, Kolkata, 700152, West Bengal, India

    Anupam Ghosh

  4. Department of CSE, University of Calcutta, Kolkata, 700073, West Bengal, India

    Kashi Nath Dey

Authors
  1. Sujay Saha
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  2. Priyojit Das
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  3. Anupam Ghosh
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  4. Kashi Nath Dey
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Corresponding author

Correspondence to Sujay Saha .

Editor information

Editors and Affiliations

  1. University of KwaZulu-Natal, Durban, South Africa

    Mayank Singh

  2. Jaypee University of Information Technology, Solan, India

    P. K. Gupta

  3. Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

    Vipin Tyagi

  4. Institute of Information Theory and Automation, Prague 8, Czech Republic

    Jan Flusser

  5. University of Ottawa, Ottawa, Canada

    Tuncer Ören

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Saha, S., Das, P., Ghosh, A., Dey, K.N. (2018). Ranking of Cancer Mediating Genes: A Novel Approach Using Genetic Algorithm in DNA Microarray Gene Expression Dataset. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 906. Springer, Singapore. https://doi.org/10.1007/978-981-13-1813-9_13

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  • DOI: https://doi.org/10.1007/978-981-13-1813-9_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1812-2

  • Online ISBN: 978-981-13-1813-9

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