Full Paper View Go Back

Prediction of HIV Replication in the Human Immune System using Multinomial Distribution by Bayesian Methodology

G. Meenakshi1 , P.R. Maheswari2

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.1 , pp.46-52, Feb-2019


CrossRef-DOI:   https://doi.org/10.26438/ijsrmss/v6i1.4652


Online published on Feb 28, 2019


Copyright © G. Meenakshi, P.R. Maheswari . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

View this paper at   Google Scholar | DPI Digital Library


XML View     PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: G. Meenakshi, P.R. Maheswari, “Prediction of HIV Replication in the Human Immune System using Multinomial Distribution by Bayesian Methodology,” International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.6, Issue.1, pp.46-52, 2019.

MLA Style Citation: G. Meenakshi, P.R. Maheswari "Prediction of HIV Replication in the Human Immune System using Multinomial Distribution by Bayesian Methodology." International Journal of Scientific Research in Mathematical and Statistical Sciences 6.1 (2019): 46-52.

APA Style Citation: G. Meenakshi, P.R. Maheswari, (2019). Prediction of HIV Replication in the Human Immune System using Multinomial Distribution by Bayesian Methodology. International Journal of Scientific Research in Mathematical and Statistical Sciences, 6(1), 46-52.

BibTex Style Citation:
@article{Meenakshi_2019,
author = {G. Meenakshi, P.R. Maheswari},
title = {Prediction of HIV Replication in the Human Immune System using Multinomial Distribution by Bayesian Methodology},
journal = {International Journal of Scientific Research in Mathematical and Statistical Sciences},
issue_date = {2 2019},
volume = {6},
Issue = {1},
month = {2},
year = {2019},
issn = {2347-2693},
pages = {46-52},
url = {https://www.isroset.org/journal/IJSRMSS/full_paper_view.php?paper_id=1139},
doi = {https://doi.org/10.26438/ijcse/v6i1.4652}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i1.4652}
UR - https://www.isroset.org/journal/IJSRMSS/full_paper_view.php?paper_id=1139
TI - Prediction of HIV Replication in the Human Immune System using Multinomial Distribution by Bayesian Methodology
T2 - International Journal of Scientific Research in Mathematical and Statistical Sciences
AU - G. Meenakshi, P.R. Maheswari
PY - 2019
DA - 2019/02/28
PB - IJCSE, Indore, INDIA
SP - 46-52
IS - 1
VL - 6
SN - 2347-2693
ER -

635 Views    667 Downloads    106 Downloads
  
  

Abstract :
For the last four decades the treatment of the HIV infection is very complicated. There are many Statistical and Mathematical models have been developed for the HIV replication. Most of them are system of linear differential equations. But parameter estimation and analytical solution of the differential equations is not easy to obtain. So, this paper concentrated to predict the viral replication based on the determination of the four categories of CD_4^+ T cells classification as multinomial distribution and also used the Bayesian methodology with conjugate prior of Dirichlet distribution.

Key-Words / Index Term :
Bayesian Methodology,〖CD〗_4^+ T cells, Dirichlet Distribution, HIV Replication, Multinomial Distribution

References :
[1] M. Eigen and R. Winkler – Oswatitsch, “Steps towards life: A perspective on evolution”,Oxford University Press, Oxford, pp 173, 1992.
[2] M.Eigen, “ The origin of genetic information : viruses as models”, Elsevier,vol.135,issue.1-2 pp 37-47,1993.
[3] J. M. Coffin. “HIV population dynamics in vivo: implications for genetic variations, pathogenesis, and therapy”, Science,vol.267,pp 483 – 489, 1995.
[4] A. J. Leigh Brown, and D. D. Richman, “HIV – 1: gambling on the evolution of drug resistance”, Nature Medicine 3,pp 268 – 271, 1997.
[5] A. J. Leigh Brown, “Analysis of HIV – 1 env gene sequences reveals evidence for a low effective number in the viral population”, Proc.Natl.Acad.Sci USA,vol. 97,pp 1862 – 1865,1997.
[6] O.Davidov, “The steady state probabilities for a regenerative semi – Markov processes with application to prevention and screaming”, Applied Stochastic Models and Data Analysis, Vol.15, No.1, pp. 55 – 63, 1999.
[7] O.Davidov and M. Zelen, “Designing Cancer Prevention Trials: a Stochastic model approach”, Statistics in Medicine, Vol.19, issue.15, pp. 1983 – 1995, 2000.
[8] G.D. Biase and et.al, “A Stochastic model for the HIV/AIDS dynamic evolution”, Hindawi Publishing Corporation Mathematical problems in Engineering, vol.2007, Article ID.65636, 14 Pages doi: 10.1155/2007/65636,2007.
[9] R. Lakshmajayam and G.Meenakshi “HIV Replication Model for the Succeeding Period of Viral Dynamic Studies In Aids Clinical Trials” International Journal Of Mathematics And Statistics Invention (IJMSI) Volume 2 Issue 10 PP-28-36, 2014.
[10] S.Sharma et.al “Predictive analysis using classification techniques in healthcare domain” International Journal of Computer Sciences and Engineering,vol. 6,issue.2 ,pp 206 -212,2018.

Authorization Required

 

You do not have rights to view the full text article.
Please contact administration for subscription to Journal or individual article.
Mail us at  support@isroset.org or view contact page for more details.

Go to Navigation