IDEAS home Printed from https://ideas.repec.org/a/adm/journl/v2y2013i6p24-33.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.ijsciences.com/pub/article/187
    Download Restriction: no
    File URL: https://www.ijsciences.com/pub/pdf/V2-201306-02.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David Baker, 2000. "A surprising simplicity to protein folding," Nature, Nature, vol. 405(6782), pages 39-42, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yaman Arkun & Mert Gur, 2012. "Combining Optimal Control Theory and Molecular Dynamics for Protein Folding," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-8, January.
    2. Stefano Zamuner & Flavio Seno & Antonio Trovato, 2022. "Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-20, January.
    3. Seth Lichter & Benjamin Rafferty & Zachary Flohr & Ashlie Martini, 2012. "Protein High-Force Pulling Simulations Yield Low-Force Results," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-10, April.
    4. Amit K Chattopadhyay & Biswajit Debnath & Rihab El-Hassani & Sadhan Kumar Ghosh & Rahul Baidya, 2020. "Cleaner Production in Optimized Multivariate Networks: Operations Management through a Roll of Dice," Papers 2003.00884, arXiv.org.
    5. Omar Haq & Michael Andrec & Alexandre V Morozov & Ronald M Levy, 2012. "Correlated Electrostatic Mutations Provide a Reservoir of Stability in HIV Protease," PLOS Computational Biology, Public Library of Science, vol. 8(9), pages 1-10, September.
    6. Yaman Arkun & Burak Erman, 2010. "Prediction of Optimal Folding Routes of Proteins That Satisfy the Principle of Lowest Entropy Loss: Dynamic Contact Maps and Optimal Control," PLOS ONE, Public Library of Science, vol. 5(10), pages 1-11, October.
    7. Christopher A Brown & Kevin S Brown, 2010. "Validation of Coevolving Residue Algorithms via Pipeline Sensitivity Analysis: ELSC and OMES and ZNMI, Oh My!," PLOS ONE, Public Library of Science, vol. 5(6), pages 1-14, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:adm:journl:v:2:y:2013:i:6:p:24-33. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Staff ijSciences (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.