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Mutual Information –The Biomarker of Essential Gene Predictions in Gene-Gene-Interaction of Lung Cancer

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Computational Intelligence, Communications, and Business Analytics (CICBA 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1031))

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Abstract

Lung cancer is a biggest epidemic in current decade. Recent statistical results clearly accounted that higher percentage of male and female had been under its trap. Researchers are engaged by themselves to reduce its percentage periodically. It is observed that macromolecules acted as an essential role in this improvement. One of the important macromolecules of life is gene and its complex. Genes in interaction participates in more number of functional activities as compared to individuals. Normally, similar set i.e. functionally similar set of genes stay in same network. Initially the proposed work starts with gene expression microarray dataset which consists of sets of both normal as well as disease gene samples. A total collection of 7129 genes are involved in the dataset out of which 3556 variant set of genes have been filtered out by applying two-tailed T-test. Hence Mutual information and K -means clustering algorithms are executed on these variant set of genes to obtain most similar set of genes. Interactions of these filtered genes have been studied using String DB and Gene Mania from where the most reliable genes have been retained using node and edge weight. 109 most reliable genes are finally identified as diver nodes or controller genes which can play an essential role in lung cancer. Our methodology achieves an overall accuracy of 88%.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Sudhir Ch. Sur Degree Engineering College, Dumdum, 700074, Kolkata, India

    Anjan Kumar Payra

  2. Department of Computer Science and Engineering, Netaji Subhash Engineering College, Garia, 700152, Kolkata, India

    Anupam Ghosh

Authors
  1. Anjan Kumar Payra
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  2. Anupam Ghosh
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Corresponding author

Correspondence to Anjan Kumar Payra .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    Jyotsna Kumar Mandal

  2. Department of Computer Science and Engineering, Assam University, Silchar, Assam, India

    Somnath Mukhopadhyay

  3. Department of Computer and Systems Sciences, Visva Bharati University, Santiniketan, West Bengal, India

    Paramartha Dutta

  4. Department of Computer Science and Engineering, Kalyani Government Engineering College, Kalyani, West Bengal, India

    Kousik Dasgupta

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Payra, A.K., Ghosh, A. (2019). Mutual Information –The Biomarker of Essential Gene Predictions in Gene-Gene-Interaction of Lung Cancer. In: Mandal, J., Mukhopadhyay, S., Dutta, P., Dasgupta, K. (eds) Computational Intelligence, Communications, and Business Analytics. CICBA 2018. Communications in Computer and Information Science, vol 1031. Springer, Singapore. https://doi.org/10.1007/978-981-13-8581-0_19

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  • DOI: https://doi.org/10.1007/978-981-13-8581-0_19

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-8580-3

  • Online ISBN: 978-981-13-8581-0

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