Functional Classification of Genes Using Non-Negative Independent Component Analysis

  • Monica Chagoyen
  • Hugo Fernandes
  • Jose M. Carazo
  • Alberto Pascual-Montano
Conference paper
Part of the Mathematics in Industry book series (MATHINDUSTRY, volume 12)

In the last few years, several analysis methods have been proposed to assist in the functional interpretation of genome-wide data. To this aim, we explore the use of non-negative Independent Component Analysis (nnICA) for the classifi- cation of genes based on their associated functional annotations.

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References

  1. 1.
    Homayouni, R. and Heinrich, K. and Wei, L. and Berry, M. W. Gene clustering by latent semantic indexing of MEDLINE abstracts. Bioinformatics 21, 104-15 2005.CrossRefGoogle Scholar
  2. 2.
    Chagoyen, M. and Carmona-Saez, P. and Shatkay, H. and Carazo, J. M. and Pascual-Montano, A. Discovering semantic features in the literature: a foundation for building functional associations. BMC Bioinformatics 7, 41 2006.CrossRefGoogle Scholar
  3. 3.
    Chagoyen, M. and Carmona-Saez, P. and Gil, C. and Carazo, J. M. and Pascual- Montano, A. A literature-based similarity metric for biological processes. BMC Bioinformatics 7, 363 2006.CrossRefGoogle Scholar
  4. 4.
    Khatri, P. and Done, B. and Rao, A. and Done, A. and Draghici, S. A semantic analysis of the annotations of the human genome. Bioinformatics 21, 3416 2005.CrossRefGoogle Scholar
  5. 5.
    Bodenreider, O. and Aubry, M. and Burgun, A. Non-lexical approaches to iden- tifying associative relations in the gene ontology. Pac Symp Biocomput 91-102 (2005).Google Scholar
  6. 6.
    Pehkonen, P. and Wong, G. and Toronen, P. Theme discovery from gene lists for identification and viewing of multiple functional groups. BMC Bioinformatics 6 1,162 2005.CrossRefGoogle Scholar
  7. 7.
    Plumbley, M. D. Algorithms for nonnegative independent component analysis. IEEE Transactions on Neural Networks 14, 534-543 2003.CrossRefGoogle Scholar
  8. 8.
    Plumbley, M. D. Optimization using Fourier expansion over a geodesic for non- negative ICA. Independent Component Analysis and Blind Signal Separation 3195,49-56 2004.Google Scholar
  9. 9.
    Ashburner, M. et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 251, 25-9 2000.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Monica Chagoyen
    • 1
    • 3
  • Hugo Fernandes
    • 2
  • Jose M. Carazo
    • 1
  • Alberto Pascual-Montano
    • 3
  1. 1.Biocomputing UnitCentro Nacional de Biotecnologia - CSICMadridSpain
  2. 2.Integromics S.L.GranadaSpain
  3. 3.Biocomputing UnitCentro Nacional de Biotecnologia - CSICMadridSpain

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