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A Clustering Strategy to Find Similarities in Mycoplasma Promoters

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Advances in Bioinformatics and Computational Biology (BSB 2005)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 3594))

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Abstract

This paper presents a neural network clustering strategy to identify regularities in a dataset of Mycoplasma promoter sequences. The traditional way that prokaryotic promoters are identified is proven inadequate to the Mycoplasma family. Our clustering approach tries to discover regularities in base pair compositions of the dataset sequences to give clues which indicate the presence or absence of promoters. Several experiments with leave-one-out strategy and a negative dataset revealed a best way to fit model parameters. Preliminary results are promising for creating a computational model able to find promoter regions in Mycoplasmas.

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References

  1. Carpenter, G.A., Grossberg, S.: ART2: self-organization of stable category recognition codes for analog input patterns. Applied Optics 26(23), 4919–4930 (1987)

    Article  Google Scholar 

  2. Cooper, G.M., Hausman, R.E.: The Cell: A Molecular Approach 3rd edn. Amer. Soc. Microbiol., Washington and Sinauer Assoc., Sunderland, MA (2003)

    Google Scholar 

  3. Fyfe, C.: Artificial Neural Networks. Departmant of Computing and Information Systems. The University of Paisley, Scotland (1996)

    Google Scholar 

  4. Herrmann, R.: Molecular Biology of the Bacterium Mycoplasma pneumoniae. Report. Zentrum für Molekulare Biologie Heidelberg. Universität Heidelberg. Germany (2002)

    Google Scholar 

  5. Lewin, B.: Genes VII. Oxford University Press, New York (1999)

    Google Scholar 

  6. Valiati, J.F.: Reconhecimento de Voz para Comando de Direcionamento por Meio de Redes Neurais. PPGC da UFRGS. Porto Alegre (2000)

    Google Scholar 

  7. Weiner III, J., Herrmann, R., Browning, G.F.: Transcription in Mycoplasma pneumoniae. Nucleic Acids Research 28, 4488–4496 (2000)

    Article  Google Scholar 

  8. Wu, C.H., McLarty, J.M.: Neural Networks and Genome Informatics. Elsevier Science, New York (2000)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Instituto de Informática, Universidade Federal do Rio Grande do Sul, C. Box 15.064, 91.501-970, Porto Alegre, RS, Brazil

    João Francisco Valiati & Paulo Martins Engel

Authors
  1. João Francisco Valiati
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  2. Paulo Martins Engel
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Virginia Bioinformatics Institute and Virginia Polytechnic Institute and State University, Bioinformatics 1, Box 0477, 24060-0477, Blacksburg, VA, USA

    João Carlos Setubal

  2. Instituto de Quimica, Departamento de Bioquimica, Universidade de Sao Paulo, Av. Prof. Lineu Prestes 748, 05508-000, Sao Paulo, SP, Brazil

    Sergio Verjovski-Almeida

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© 2005 Springer-Verlag Berlin Heidelberg

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Valiati, J.F., Engel, P.M. (2005). A Clustering Strategy to Find Similarities in Mycoplasma Promoters. In: Setubal, J.C., Verjovski-Almeida, S. (eds) Advances in Bioinformatics and Computational Biology. BSB 2005. Lecture Notes in Computer Science(), vol 3594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11532323_33

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  • DOI: https://doi.org/10.1007/11532323_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28008-8

  • Online ISBN: 978-3-540-31861-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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