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A New Approach for Clustering Gene Expression Data

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Computational Intelligence, Communications, and Business Analytics (CICBA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 776))

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Abstract

Most of the clustering algorithms are sensitive to noise. Many of them cluster all the genes of the dataset. However, it may be possible that only a small part of genes of the gene expression dataset is involved in the biological processes for a particular set of experiment conditions or sample. To identify these genes clusters, we propose a method which identifies the co-expressed genes having chances of co-regulation in presence of non-functional genes and high level of noise. The proposed method clusters those genes that are within distance threshold t with respect to a specific gene in each experiment conditions and works on column wise distance calculation approach. To validate the proposed method an experimental analysis has been done with a real gene expression data and the experimental results show the significance of proposed method over existing one.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Patna, Bihar, India

    Girish Chandra & Sudhakar Tripathi

Authors
  1. Girish Chandra
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  2. Sudhakar Tripathi
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Corresponding author

Correspondence to Girish Chandra .

Editor information

Editors and Affiliations

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

    J. K. Mandal

  2. Department of Computer and System Sciences, Visva Bharati University, Bolpur Santiniketan, West Bengal, India

    Paramartha Dutta

  3. Department of Information Technology, Calcutta Business School, Kolkata, India

    Somnath Mukhopadhyay

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Chandra, G., Tripathi, S. (2017). A New Approach for Clustering Gene Expression Data. In: Mandal, J., Dutta, P., Mukhopadhyay, S. (eds) Computational Intelligence, Communications, and Business Analytics. CICBA 2017. Communications in Computer and Information Science, vol 776. Springer, Singapore. https://doi.org/10.1007/978-981-10-6430-2_5

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  • DOI: https://doi.org/10.1007/978-981-10-6430-2_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6429-6

  • Online ISBN: 978-981-10-6430-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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