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A Deeply Glimpse into Protein Fold Recognition

Author

Listed:
  • Marwa Mohammed M. Ghareeb
  • Ahmed Sharaf Eldin
  • Taysir Hassan A. Soliman
  • Mohammed Ebrahim Marie

Abstract

The rapid growth in genomic and proteomic data causes a lot of challenges that are raised up and need powerful solutions. It is worth noting that UniProtKB/TrEMBL database Release 28-Nov-2012 contains 28,395,832 protein sequence entries, while the number of stored protein structures in Protein Data Bank (PDB, 4-12-2012) is 65,643. Thus, the need of extracting structural information through computational analysis of protein sequences has become very important, especially, the prediction of the fold of a query protein from its primary sequence has become very challenging. The traditional computational methods are not powerful enough to address theses challenges. Researchers have examined the use of a lot of techniques such as neural networks, Monte Carlo, support vector machine and data mining techniques. This paper puts a spot on this growing field and covers the main approaches and perspectives to handle this problem.

Suggested Citation

  • Marwa Mohammed M. Ghareeb & Ahmed Sharaf Eldin & Taysir Hassan A. Soliman & Mohammed Ebrahim Marie, 2013. "A Deeply Glimpse into Protein Fold Recognition," International Journal of Sciences, Office ijSciences, vol. 2(06), pages 24-33, June.
    • Handle: RePEc:adm:journl:v:2:y:2013:i:6:p:24-33
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    References listed on IDEAS

    as
    1. David Baker, 2000. "A surprising simplicity to protein folding," Nature, Nature, vol. 405(6782), pages 39-42, May.
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