A Framework for Query Optimization Algorithms for Biological Data

Authors

Keywords:

Query Optimization, Searching Algorithms, bioinformatics, parallel computing

Abstract

Recently, the size of biological databases has significantly increased, with a growing number of users and rates of queries. As a result, some databases have reached a terabyte size. On the other hand, the need to access the databases at the fastest possible rates is increasing. At this point, the computer scientists could assist to organize the data and query in a way that allows biologists to quickly search existing information. In this paper, a query model for DNA and protein sequence datasets is proposed. This method of dealing with the query can effectively and rapidly retrieve all similar proteins/DNA from a large database. A theoretical and conceptual proposed framework is derived using query techniques form different applications. The results show that the query optimization algorithms reduce the query processing time in comparison with the normal query searching algorithm.

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Published

2019-07-31

How to Cite

JABER, K. M., A. HAMAD, N., & M. QUIAM, F. (2019). A Framework for Query Optimization Algorithms for Biological Data. International Journal of Computational and Experimental Science and Engineering, 5(2), 76–79. Retrieved from https://ijcesen.com/index.php/ijcesen/article/view/92

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Section

Research Article