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Efficient Biclustering Algorithms for Time Series Gene Expression Data Analysis

  • Conference paper
Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living (IWANN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5518))

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Abstract

We present a summary of a PhD thesis proposing efficient biclustering algorithms for time series gene expression data analysis, able to discover important aspects of gene regulation as anticorrelation and time-lagged relationships, and a scoring method based on statistical significance and similarity measures. The ability of the proposed algorithms to efficiently identify sets of genes with statistically significant and biologically meaningful expression patterns is shown to be instrumental in the discovery of relevant biological phenomena, leading to more convincing evidence of specific transcriptional regulatory mechanisms.

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References

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Author information

Authors and Affiliations

  1. Instituto Superior Tcnico, Technical University of Lisbon, Portugal

    Sara C. Madeira & Arlindo L. Oliveira

  2. Knowledge Discovery and Bioinformatics (KDBIO) Group, INESC-ID, Portugal

    Sara C. Madeira & Arlindo L. Oliveira

  3. University of Beira Interior, Portugal

    Sara C. Madeira

Authors
  1. Sara C. Madeira
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  2. Arlindo L. Oliveira
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Editor information

Editors and Affiliations

  1. Graduate School of Engineering, Osaka Prefecture University, Osaka, Japan

    Sigeru Omatu

  2. Department of Informatics / CCTC, University of Minho, Braga, Portugal

    Miguel P. Rocha

  3. MAmI Research Lab, University of Castilla-La Mancha,, Ciudad Real, Spain

    José Bravo

  4. Department of Informatics, University of Vigo, Ourense, Spain

    Florentino Fernández

  5. Grupo de Investigación GICAP, Área de Lenguajes Higher Polytechnic School, Universidad de Burgos, Burgos, Spain

    Emilio Corchado

  6. Higher Polytechnic School, University of Burgos, Burgos, Spain

    Andrés Bustillo

  7. Department of Informatics, University of Salamanca, Salamanca, Spain

    Juan M. Corchado

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© 2009 Springer-Verlag Berlin Heidelberg

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Madeira, S.C., Oliveira, A.L. (2009). Efficient Biclustering Algorithms for Time Series Gene Expression Data Analysis. In: Omatu, S., et al. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN 2009. Lecture Notes in Computer Science, vol 5518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02481-8_154

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  • DOI: https://doi.org/10.1007/978-3-642-02481-8_154

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02480-1

  • Online ISBN: 978-3-642-02481-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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