References
I would like to thank my supervisor Dr. Nick Jones and Juvid Aryaman for their help and advice throughout this project.
The project was based on the following research:
- Goll, R., Olsen, T., Cui, G. and Florholmen, J., 2006. Evaluation of absolute quantitation by nonlinear regression in probe-based real-time PCR. BMC bioinformatics, 7(1), p.107. [Article]
- Haario, H., Saksman, E. and Tamminen, J., 2001. An adaptive Metropolis algorithm. Bernoulli, 7(2), pp.223-242. [Article]
- Heid, C.A., Stevens, J., Livak, K.J. and Williams, P.M., 1996. Real time quantitative PCR. Genome research, 6(10), pp.986-994. [Article]
- Hoitzing, H., Gammage, P.A., Minczuk, M., Johnston, I.G. and Jones, N.S., 2017. Energetic Costs Of Cellular And Therapeutic Control Of Stochastic mtDNA Populations. bioRxiv, p.145292. [Article]
- Lalam, N., 2007. Statistical inference for quantitative polymerase chain reaction using a hidden markov model: a Bayesian approach. Statistical applications in genetics and molecular biology, 6(1). [Article]
- Schmittgen, T.D. and Livak, K.J., 2008. Analyzing real-time PCR data by the comparative CT method. Nature protocols, 3(6), pp.1101-1108. [Article]
- Stewart, J.B. and Chinnery, P.F., 2015. The dynamics of mitochondrial DNA heteroplasmy: implications for human health and disease. Nature Reviews Genetics, 16(9), pp.530-542. [Article]
- Wallace, D.C. and Chalkia, D., 2013. Mitochondrial DNA genetics and the heteroplasmy conundrum in evolution and disease. Cold Spring Harbor perspectives in biology, 5(11), p.a021220. [Article]
- Wilkinson, D.J., 2011. Stochastic modelling for systems biology. CRC press.