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Oligonucleotide Microarray Probe Correction by FixedPoint ICA Algorithm

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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

Oligonucleotide Microarrays have become powerful tools in genetics, as they serve as parallel scanning mechanisms to detect the presence of genes using test probes. The detection of each gene depends on the multichannel differential expression of perfectly matched segments against mismatched ones. This methodology posse some interesting problems under the point of view of Genomic Signal Processing, as test probes express themselves in rather different patterns, not showing proportional expression levels for most of the segment pairs, as it would be expected. The method proposed in this paper consists in isolating gene expressions showing unexpected behavior using independent component analysis.

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References

  1. Bellenson, J.L.: Expression data and the bioinformatics challenges. In: Schena, M. (ed.) DNA Microarrays, pp. 139–165. Oxford University Press, Oxford (1999)

    Google Scholar 

  2. Whitchurch, A.K.: Gene expression microarrays. IEEE Potentials 21, 30–34 (2002)

    Article  Google Scholar 

  3. Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. Wiley, NJ (2001)

    Book  Google Scholar 

  4. Cichocki, A., Amari, S.: Adaptive Blind Signal and Image Processing Learning algorithms and applications. Wiley, NJ (2002)

    Google Scholar 

  5. Malutan, R., Gómez, P., Díaz, F., Martinez, R., Rodellar, V., Borda, M.: Modeling Diachronical Hybridization Microarray Data. In: Cristea, P.D., Tabus, I., Tuduce, R. (eds.) NSIP 2007, Bucharest, pp. 174–178 (2007)

    Google Scholar 

  6. Centro Nacional de Investigaciones Oncologicas, http://www.cnio.es/ing/

  7. Firestein Neuro-Biology Lab, http://firestein.bio.columbia.edu/

  8. Center for the Study of Biological Complexity, http://www.vcu.edu/csbc/

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Author information

Authors and Affiliations

  1. Technical University of Cluj-Napoca, George Baritiu, nº 26-28, 400027, Cluj-Napoca, Romania

    Raul Malutan & Monica Borda

  2. Universidad Politécnica de Madrid, Campus de Montegancedo, s/n, 28660, Boadilla del Monte, Madrid, Spain

    Raul Malutan & Pedro Gómez

Authors
  1. Raul Malutan
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  2. Pedro Gómez
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  3. Monica Borda
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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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Malutan, R., Gómez, P., Borda, M. (2009). Oligonucleotide Microarray Probe Correction by FixedPoint ICA Algorithm. 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_150

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  • DOI: https://doi.org/10.1007/978-3-642-02481-8_150

  • 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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