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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 4, 2019.
Abstract: The RNA sequence editing has become a challenging task in the molecular computing. There are number of approaches that have been discussed earlier for the problem RNA editing in bio molecular computing, but they suffer to achieve higher performance. To improve the performance, an real time approach has been presented which uses sequence depth measure (SDM). The method receives the RNA sequence and estimates the depth measure for different sub sequences generated. Based on the SDM value, a cumulative sequence match measure (SMM) has been measured to classify the sequence towards the different classes available. The matrix insertion and deletion is performed based on the template match measure (TMM) which has been computed based on the matches found in the templates available for different classes. The experimental results of our approach prove to outperform in terms of Accuracy, Risk Detection Accuracy, Time Complexity and False Classification Ratio which in turn increases the performance of bio molecular computing and matrix insertion deletion.
Kotteeswaran C, Khanaa V and Rajesh A, “Real Time RNA Sequence Edition with Matrix Insertion Deletion for Improved Bio Molecular Computing using Template Match Measure” International Journal of Advanced Computer Science and Applications(IJACSA), 10(4), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100454
@article{C2019,
title = {Real Time RNA Sequence Edition with Matrix Insertion Deletion for Improved Bio Molecular Computing using Template Match Measure},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100454},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100454},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {4},
author = {Kotteeswaran C and Khanaa V and Rajesh A}
}
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.