PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Bayesian approach of Quantitative Polymerase Chain Reaction
Nadia Lalam and Christine Jacob
In: European Conference on Mathematical and Theoretical Biology, 18-22 Jul 2005, Dresden, Germany.

Abstract

Quantitative Polymerase Chain Reaction aims at determining the initial amount $X_0$ of a specific portion of DNA molecules from the observation of the amplification process of the DNA molecules quantity. This amplification process is achieved through successive replication cycles. It depends on the efficiency $\{p_n\}_n$ of the replication of the molecules, $p_n$ being the probability that a molecule will duplicate at replication cycle $n$. Modelling the amplification process by a branching process and assuming $p_n=p$ for all $n$, we estimate the unknown parameter $\theta=(p, X_0)$ using Markov Chain Monte Carlo methods under a Bayesian framework.

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EPrint Type:Conference or Workshop Item (Talk)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:1467
Deposited By:Nadia Lalam
Deposited On:28 November 2005