Computational Biology and Bioinformatics

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Protein Function Prediction Using Neighbor Counting with Dynamic Threshold from Protein-Protein Interaction Network

Received: 10 January 2015    Accepted: 26 January 2015    Published: 02 February 2015
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Abstract

In recent years, a large number of proteins of different organisms have been discovered but due to high experimental cost and uncertain time boundary, yet it is not possible to find out all of the functionalities of those proteins. With the recent advent of huge protein-protein interactions, it becomes an opportunity to computationally predict a protein’s functionality based on its interacting partners. In this work, we mainly try to find out a way by which we can predict functionality of a target protein with low computational complexity. We propose a simple approach for protein function prediction based on Classical Neighbor Counting method. We also investigate the functional dependency of a protein to its direct neighbors in the interaction network. We find that when majority of its interacting partners have more experimentally known annotation, then more accurately we can predict a protein’s functionality using Neighbor Counting technique.

DOI 10.11648/j.cbb.20150301.11
Published in Computational Biology and Bioinformatics (Volume 3, Issue 1, February 2015)
Page(s) 1-5
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Protein Function Prediction, Neighbor Counting with Dynamic Threshold, Protein-Protein Interaction Network

References
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[15] Michael Ashburner, et al., “Gene Ontology: Tool for the unification of biology”, Nature Genetics 25, 25 – 29, 2000.
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Author Information
  • Department of Computer Science & Engineering, Pabna University of Science & Technology, Pabna, Bangladesh

  • Department of Computer Science & Engineering, Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh

  • Department of Computer Science & Engineering, Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh

  • Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh

Cite This Article
  • APA Style

    Md. Khaled Ben Islam, Julia Rahman, Md. Al Mehedi Hasan, Mohammed Nasser. (2015). Protein Function Prediction Using Neighbor Counting with Dynamic Threshold from Protein-Protein Interaction Network. Computational Biology and Bioinformatics, 3(1), 1-5. https://doi.org/10.11648/j.cbb.20150301.11

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    ACS Style

    Md. Khaled Ben Islam; Julia Rahman; Md. Al Mehedi Hasan; Mohammed Nasser. Protein Function Prediction Using Neighbor Counting with Dynamic Threshold from Protein-Protein Interaction Network. Comput. Biol. Bioinform. 2015, 3(1), 1-5. doi: 10.11648/j.cbb.20150301.11

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    AMA Style

    Md. Khaled Ben Islam, Julia Rahman, Md. Al Mehedi Hasan, Mohammed Nasser. Protein Function Prediction Using Neighbor Counting with Dynamic Threshold from Protein-Protein Interaction Network. Comput Biol Bioinform. 2015;3(1):1-5. doi: 10.11648/j.cbb.20150301.11

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  • @article{10.11648/j.cbb.20150301.11,
      author = {Md. Khaled Ben Islam and Julia Rahman and Md. Al Mehedi Hasan and Mohammed Nasser},
      title = {Protein Function Prediction Using Neighbor Counting with Dynamic Threshold from Protein-Protein Interaction Network},
      journal = {Computational Biology and Bioinformatics},
      volume = {3},
      number = {1},
      pages = {1-5},
      doi = {10.11648/j.cbb.20150301.11},
      url = {https://doi.org/10.11648/j.cbb.20150301.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.cbb.20150301.11},
      abstract = {In recent years, a large number of proteins of different organisms have been discovered but due to high experimental cost and uncertain time boundary, yet it is not possible to find out all of the functionalities of those proteins. With the recent advent of huge protein-protein interactions, it becomes an opportunity to computationally predict a protein’s functionality based on its interacting partners. In this work, we mainly try to find out a way by which we can predict functionality of a target protein with low computational complexity. We propose a simple approach for protein function prediction based on Classical Neighbor Counting method. We also investigate the functional dependency of a protein to its direct neighbors in the interaction network. We find that when majority of its interacting partners have more experimentally known annotation, then more accurately we can predict a protein’s functionality using Neighbor Counting technique.},
     year = {2015}
    }
    

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    T1  - Protein Function Prediction Using Neighbor Counting with Dynamic Threshold from Protein-Protein Interaction Network
    AU  - Md. Khaled Ben Islam
    AU  - Julia Rahman
    AU  - Md. Al Mehedi Hasan
    AU  - Mohammed Nasser
    Y1  - 2015/02/02
    PY  - 2015
    N1  - https://doi.org/10.11648/j.cbb.20150301.11
    DO  - 10.11648/j.cbb.20150301.11
    T2  - Computational Biology and Bioinformatics
    JF  - Computational Biology and Bioinformatics
    JO  - Computational Biology and Bioinformatics
    SP  - 1
    EP  - 5
    PB  - Science Publishing Group
    SN  - 2330-8281
    UR  - https://doi.org/10.11648/j.cbb.20150301.11
    AB  - In recent years, a large number of proteins of different organisms have been discovered but due to high experimental cost and uncertain time boundary, yet it is not possible to find out all of the functionalities of those proteins. With the recent advent of huge protein-protein interactions, it becomes an opportunity to computationally predict a protein’s functionality based on its interacting partners. In this work, we mainly try to find out a way by which we can predict functionality of a target protein with low computational complexity. We propose a simple approach for protein function prediction based on Classical Neighbor Counting method. We also investigate the functional dependency of a protein to its direct neighbors in the interaction network. We find that when majority of its interacting partners have more experimentally known annotation, then more accurately we can predict a protein’s functionality using Neighbor Counting technique.
    VL  - 3
    IS  - 1
    ER  - 

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