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DOI: 10.14569/IJACSA.2017.080450
PDF

Modern Data Formats for Big Bioinformatics Data Analytics

Author 1: Shahzad Ahmed
Author 2: M. Usman Ali
Author 3: Javed Ferzund
Author 4: Muhammad Atif Sarwar
Author 5: Abbas Rehman
Author 6: Atif Mehmood

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 4, 2017.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Next Generation Sequencing (NGS) technology has resulted in massive amounts of proteomics and genomics data. This data is of no use if it is not properly analyzed. ETL (Extraction, Transformation, Loading) is an important step in designing data analytics applications. ETL requires proper understanding of features of data. Data format plays a key role in understanding of data, representation of data, space required to store data, data I/O during processing of data, intermediate results of processing, in-memory analysis of data and overall time required to process data. Different data mining and machine learning algorithms require input data in specific types and formats. This paper explores the data formats used by different tools and algorithms and also presents modern data formats that are used on Big Data Platform. It will help researchers and developers in choosing appropriate data format to be used for a particular tool or algorithm.

Keywords: Big Data; Machine Learning; Hadoop; MapReduce; Spark; Bioinformatics; Microarray; Data Models; Data Formats; Classification; Clustering

Shahzad Ahmed, M. Usman Ali, Javed Ferzund, Muhammad Atif Sarwar, Abbas Rehman and Atif Mehmood, “Modern Data Formats for Big Bioinformatics Data Analytics” International Journal of Advanced Computer Science and Applications(IJACSA), 8(4), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080450

@article{Ahmed2017,
title = {Modern Data Formats for Big Bioinformatics Data Analytics},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080450},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080450},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {4},
author = {Shahzad Ahmed and M. Usman Ali and Javed Ferzund and Muhammad Atif Sarwar and Abbas Rehman and Atif Mehmood}
}



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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