Skip to main content

On Mining Protein Unfolding Simulation Data with Inductive Logic Programming

  • Conference paper
  • 684 Accesses

Part of the book series: Advances in Soft Computing ((AINSC,volume 49))

Summary

The detailed study of folding and unfolding events in proteins is becoming central to develop rational therapeutic strategies against maladies such as Alzheimer and Parkinson disease. A promising approach to study the unfolding processes of proteins is through computer simulations. However, these computer simulations generate huge amounts of data that require computational methods for their analysis.

In this paper we report on the use of Inductive Logic Programming (ILP) techniques to analyse the trajectories of protein unfolding simulations. The paper describes ongoing work on one of several problems of interest in the protein unfolding setting. The problem we address here is that of explaining what makes secondary structure elements to break down during the unfolding process. We tackle such problem collecting examples of contexts where secondary structures break and (automatically) constructing rules that may be used to suggest the explanations.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Brito, R.M.M., Dubitzky, W., Rodrigues, J.R.: Protein folding and unfolding simulations: A new challenge for data mining. OMICS: A Journal of Integrative Biology 8, 153–166 (2004)

    Article  Google Scholar 

  2. Dzeroski, S.: Relational Data Mining. Springer, New York (2001)

    MATH  Google Scholar 

  3. Muggleton, S., De Raedt, L.: Inductive logic programming: Theory and methods. Journal of Logic Programming 19/20, 629–679 (1994)

    Article  Google Scholar 

  4. Pande, V.S., Baker, I., Chapman, J., et al.: Atomistic protein folding simulations on the submillisecond time scale using worldwide distributed computing. Biopolymers 68, 91–109 (2003)

    Article  Google Scholar 

  5. Shea, J.E., Brooks, C.L.: From folding theories to folding proteins: a review and assessment of simulation studies of protein folding and unfolding. Annu. Rev. Phys. Chem. 52, 499–535 (2001)

    Article  Google Scholar 

  6. Srinivasan, A.: The Aleph Manual (2003), http://web.comlab.ox.ac.uk/oucl/research/areas/machlearn/Aleph

Download references

Author information

Authors and Affiliations

Authors

Editor information

Juan M. Corchado Juan F. De Paz Miguel P. Rocha Florentino Fernández Riverola

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Camacho, R., Alves, A., Silva, C.G., Brito, R.M.M. (2009). On Mining Protein Unfolding Simulation Data with Inductive Logic Programming. In: Corchado, J.M., De Paz, J.F., Rocha, M.P., Fernández Riverola, F. (eds) 2nd International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2008). Advances in Soft Computing, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85861-4_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-85861-4_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85860-7

  • Online ISBN: 978-3-540-85861-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics