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.
| Published in | Computational Biology and Bioinformatics (Volume 3, Issue 1) |
| DOI | 10.11648/j.cbb.20150301.11 |
| 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), 2015. Published by Science Publishing Group |
Protein Function Prediction, Neighbor Counting with Dynamic Threshold, Protein-Protein Interaction Network
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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
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
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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Download@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://article.sciencepublishinggroup.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}
}
TY - JOUR 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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