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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 5, 2017.
Abstract: Graph is an expressive way to represent dynamic and complex relationships in highly connected data. In today’s highly connected world, general purpose graph databases are providing opportunities to experience benefits of semantically significant networks without investing on the graph infrastructure. Examples of prominent graph databases are: Neo4j, Titan and OrientDB etc. In biological OMICS landscape, Interactomics is one of the new disciplines that focuses mainly on the data modeling, data storage and retrieval of biological interaction data. Biological experiments generate prodigious amount of data in various formats(semi-structured or unstructured). The large volume of such data posses challenges for data acquisition, data integration, multiple data modalities (either data model of storage model, storage, processing and visualization. This paper aims at designing a well suited graphical data storage model for biological information which is collected from major heterogeneous biological data repositories, by using graph database.
Hina Farooq, Javed Ferzund, Azka Mahmood and Muhammad Atif Sarwar, “Designing Graphical Data Storage Model for Gene-Protein and Gene-Gene Interaction Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 8(5), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080559
@article{Farooq2017,
title = {Designing Graphical Data Storage Model for Gene-Protein and Gene-Gene Interaction Networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080559},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080559},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {5},
author = {Hina Farooq and Javed Ferzund and Azka Mahmood and Muhammad Atif Sarwar}
}
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.