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A Novel Approach for Biclustering Gene Expression Data Using Modular Singular Value Decomposition

  • Conference paper
Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2009)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6160))

Abstract

Clustering is a method of unsupervised learning, and a common technique for statistical data analysis used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Recently, biclustering (or co-clustering), performing simultaneous clustering on the row and column dimensions of the data matrix, has been shown to be remarkably effective in a variety of applications. In this paper we propose a novel approach to biclustering gene expression data based on Modular Singular Value Decomposition (Mod-SVD). Instead of applying SVD directly on on data matrix, the proposed approach computes SVD on modular fashion. Experiments conducted on synthetic and real dataset demonstrated the effectiveness of the algorithm in gene expression data.

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Author information

Authors and Affiliations

  1. Dept. of Computer and Information Sciences, University of Genova, Via Dodecaneso 35, 16146, Genova, Italy

    V. N. Manjunath Aradhya, Francesco Masulli & Stefano Rovetta

  2. Dept. of ISE, Dayananda Sagar College of Engg, Bangalore, India, 560078

    V. N. Manjunath Aradhya

  3. Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, Temple University, BioLife Science Bldg., 1900 N 12th Street, Philadelphia, PA, 19122, USA

    Francesco Masulli

Authors
  1. V. N. Manjunath Aradhya
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  2. Francesco Masulli
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  3. Stefano Rovetta
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Editor information

Editors and Affiliations

  1. DISI - Dipartimento di Informatica e Scienze dell’Informazione, Università di Genova, Via Dodecaneso 35, 16146, Genova, Italy

    Francesco Masulli

  2. Center for Biostatistics, The Methodist Hospital Research Institute (TMHRI), Weill Cornell Medical College, Cornell University, 6565 Fannin, Suite MGJ6-031, 77030, Houston, Texas, USA

    Leif E. Peterson

  3. Dipartimento di Matematica ed Informatica, Università di Salerno, Via Ponte don Melillo, 84084, Fisciano, (Sa), Italy

    Roberto Tagliaferri

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Aradhya, V.N.M., Masulli, F., Rovetta, S. (2010). A Novel Approach for Biclustering Gene Expression Data Using Modular Singular Value Decomposition. In: Masulli, F., Peterson, L.E., Tagliaferri, R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2009. Lecture Notes in Computer Science(), vol 6160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14571-1_19

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  • DOI: https://doi.org/10.1007/978-3-642-14571-1_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14570-4

  • Online ISBN: 978-3-642-14571-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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