CFP last date
22 April 2024
Reseach Article

Quantum Computing-Applications in Bioinformatics

by Divya Baiskhiyar, Ravi Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 12
Year of Publication: 2019
Authors: Divya Baiskhiyar, Ravi Kumar
10.5120/ijca2019919527

Divya Baiskhiyar, Ravi Kumar . Quantum Computing-Applications in Bioinformatics. International Journal of Computer Applications. 177, 12 ( Oct 2019), 26-28. DOI=10.5120/ijca2019919527

@article{ 10.5120/ijca2019919527,
author = { Divya Baiskhiyar, Ravi Kumar },
title = { Quantum Computing-Applications in Bioinformatics },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2019 },
volume = { 177 },
number = { 12 },
month = { Oct },
year = { 2019 },
issn = { 0975-8887 },
pages = { 26-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number12/30951-2019919527/ },
doi = { 10.5120/ijca2019919527 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:45:42.141278+05:30
%A Divya Baiskhiyar
%A Ravi Kumar
%T Quantum Computing-Applications in Bioinformatics
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 12
%P 26-28
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Quantum computing is a promising field that emerged out of a combination of quantum physics and computer science. With ever expanding data across different areas, the conventional computer will run out of its capacity to handle such big data. Further, extracting the meaningful from big complex data still, accompany challenges with it. Quantum computing main goal is to provide such algorithms which are robust and faster in solving problems as compared to classical computers. In this paper, the limitations of a classical computer, basic features of quantum computing and its applications in the bioinformatics have been explored.

References
  1. Moore, G, E. 1965. Cramming More Components onto Integrated Circuits. Electronics, 38(8), 114–117.
  2. Hruska, J. 2013. Intel’s former chief architect: Moore’s law will be dead within a decade.
  3. Seabaugh, A. 2013. The Tunneling Transistor. IEEE Spectrum. Retrieved from https://spectrum.ieee.org/semiconductors/devices/the-tunneling-transistor
  4. IBM. 2019. IBM Unveils World's First Integrated Quantum Computing System for Commercial Use. Retrieved from https://newsroom.ibm.com/2019-01-08-IBM-Unveils-Worlds-First-Integrated-Quantum-Computing-System-for-Commercial-Use
  5. Bennett, H. C. 1995. Quantum information and computation. Physics Today. 24-30
  6. Dirac notation
  7. Sutor, B. 2018. Scientists Prove a Quantum Computing Advantage over Classical. IBM Research Blog.
  8. Olmschenk, S. et al. 2009. Quantum teleportation between distant matter qubits. Science, 323(5913), 486–489
  9. Bazille, H. 2014. Protein design: a NP-hard problem in bioinformatics. Computer Science. 1-33
  10. Kapun, E., & Tsarev, F. 2013. De Bruijn Superwalk with Multiplicities Problem is NP-hard. BMC bioinformatics, 14 Suppl 5(Suppl 5), S7. doi:10.1186/1471-2105-14-S5-S7
  11. Just, W. 2001. Computational complexity of multiple sequence alignment with SP-score. Journal of Computational Biol biology 8(6), 615–623.
  12. Wang, L. and Jiang, T. 1994. On the complexity of multiple sequence alignment. Journal of Computational Biology, 1, 337–348.
  13. Zaslavsky, E., & Singh, M. 2006. A combinatorial optimization approach for diverse motif finding applications. Algorithms for molecular biology: AMB, 1, 13. doi:10.1186/1748-7188-1-13
  14. Li, R. Y., Felice, R. D., Rohs, R., & Lidar, D. A. 2018. Quantum annealing versus classical machine learning applied to a simplified computational biology problem. Npj Quantum Information, 4(1), 14. https://doi.org/10.1038/s41534-018-0060-8
  15. Perdomo-Ortiz, A., Dickson, N., Drew-Brook, M., Rose, G., and Aspuru-Guzik, A. 2012. Finding low-energy conformations of lattice protein models by quantum annealing. Sci Rep, 2(571). doi: 10.1038/srep00571
  16. Jain, M and Chaturvedi, S.K. 2014. Quantum Computing Based Technique for Cancer Disease Detection System. J Comput Sci Syst Biol, 7, 095-102. doi: 10.4172/jcsb.1000143
Index Terms

Computer Science
Information Sciences

Keywords

Quantum computing Classical computing Bioinformatics