IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v510y2018icp477-485.html
   My bibliography  Save this article

A novel graphical representation and similarity analysis of protein sequences based on physicochemical properties

Author

Listed:
  • Mahmoodi-Reihani, Mehri
  • Abbasitabar, Fatemeh
  • Zare-Shahabadi, Vahid

Abstract

One of popular topic in bioinformatics is protein sequence analysis. The graphical representation of protein sequence is a simple and common way to visualize protein sequences. In this study, a numerical descriptive vector for a given protein sequence is calculated based on twelve physicochemical properties of amino acids (AAs) and principal component analysis (PCA). Each entry of the descriptive vector corresponds to one AA in the sequence. By this vector, an intuitive spectrum-like graphical representation of protein sequence is proposed. Squared correlation coefficient as well as moving window correlation coefficient, as a new similarity/dissimilarity measure, were used to compare different sequences. Applicability of the proposed method is assessed by analyzing the nine ND5 proteins. The results revealed the utility of the proposed method.

Suggested Citation

  • Mahmoodi-Reihani, Mehri & Abbasitabar, Fatemeh & Zare-Shahabadi, Vahid, 2018. "A novel graphical representation and similarity analysis of protein sequences based on physicochemical properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 477-485.
  • Handle: RePEc:eee:phsmap:v:510:y:2018:i:c:p:477-485
    DOI: 10.1016/j.physa.2018.07.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118308665
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Chun & Yu, Xiaoqing & Yang, Liu & Zheng, Xiaoqi & Wang, Zhifu, 2009. "3-D maps and coupling numbers for protein sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(9), pages 1967-1972.
    2. Abo el Maaty, Moheb I. & Abo-Elkhier, Mervat M. & Abd Elwahaab, Marwa A., 2010. "3D graphical representation of protein sequences and their statistical characterization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4668-4676.
    3. He, Ping-an & Wei, Jinzhou & Yao, Yuhua & Tie, Zhixin, 2012. "A novel graphical representation of proteins and its application," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 93-99.
    Full references (including those not matched with items on IDEAS)

    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:eee:phsmap:v:510:y:2018:i:c:p:477-485. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.