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Research Article | Open Access |

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) · Vol. 8, No. 5 · Published 2017

DOI: 10.14569/IJACSA.2017.080543

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

How to Cite this Article

Sarwar, M. A., Yaseen, H., Ferzund, J., Farooq, H., & Mahmood, A. (2017). A Novel Big Data Storage Model for Protein-Protein Interaction and Gene-Protein Associations. International Journal of Advanced Computer Science and Applications, 8(5). https://doi.org/10.14569/IJACSA.2017.080543

Sarwar, M. Atif, et al.. "A Novel Big Data Storage Model for Protein-Protein Interaction and Gene-Protein Associations." International Journal of Advanced Computer Science and Applications, vol. 8, no. 5, 2017, https://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},
  volume    = {8},
  number    = {5},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {M. Atif Sarwar and Hira Yaseen and Javed Ferzund and Hina Farooq and Azka Mahmood},
  doi       = {10.14569/IJACSA.2017.080543},
  url       = {https://doi.org/10.14569/IJACSA.2017.080543}
}

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