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DOI: 10.14569/IJACSA.2017.080543
PDF

A Novel Big Data Storage Model for Protein-Protein Interaction and Gene-Protein Associations

Author 1: M. Atif Sarwar
Author 2: Hira Yaseen
Author 3: Javed Ferzund
Author 4: Hina Farooq
Author 5: Azka Mahmood

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 5, 2017.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: NGS (Next Generation Sequencing) technology has resulted in huge amount of proteomics data that exists in the form of interactions (protein-protein, gene-protein, and gene-disease). ETL (Extraction, Transformation, and Loading) techniques are very useful for Databases. Existing Rational Databases are not unified and having SQL (Structured Query Language). Proteomics data requires improvement for Integration of different Data sources. With the usage of NoSQL (not only SQL), improve the efficiency and performance. For this, a novel based unified model has been designed for protein interactions data (P-P, G-G, and G-D) by using Apache HBase to evaluate given the model, different case studies have been used.

Keywords: Hadoop; HBase; Big Data; Apache Drill; Protein-Protein Interaction; Gene-Protein Association; Gene-Disease Associations

M. Atif Sarwar, Hira Yaseen, Javed Ferzund, Hina Farooq and Azka Mahmood, “A Novel Big Data Storage Model for Protein-Protein Interaction and Gene-Protein Associations” International Journal of Advanced Computer Science and Applications(IJACSA), 8(5), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080543

@article{Sarwar2017,
title = {A Novel Big Data Storage Model for Protein-Protein Interaction and Gene-Protein Associations},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080543},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080543},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {5},
author = {M. Atif Sarwar and Hira Yaseen and Javed Ferzund and Hina Farooq and Azka Mahmood}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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