This work has its starting point in a biological experiment, in which the aim is to discover the relationship between mRNA and protein changes in a cell culture exposed to a stress. The main goal of this thesis is to provide a new analysis of the data collected by the authors of the experiment. The motivation for this study is to develop a series of advanced tools for the analysis of this kind of data. In fact, thanks to recent advances in large scale high throughput experimental methods, it will become more and more common that such data become available. It will be thus necessary to develop robust statistical methods for their analysis. This thesis wants to be a contribution in this exciting field. We first perform this analysis by reviewing the statistical methods used in the original work and by reproducing the most relevant plots using the results obtained through the analysis. In a second stage we present new, original alternative approaches and we apply these methods to analyze the data, comparing the different results obtained.

Analisi statistiche della variazione congiunta di mRNA e proteine in una coltura cellulare sottoposta a stress fisiologico

GIUSTACCHINI, LAURA
2013/2014

Abstract

This work has its starting point in a biological experiment, in which the aim is to discover the relationship between mRNA and protein changes in a cell culture exposed to a stress. The main goal of this thesis is to provide a new analysis of the data collected by the authors of the experiment. The motivation for this study is to develop a series of advanced tools for the analysis of this kind of data. In fact, thanks to recent advances in large scale high throughput experimental methods, it will become more and more common that such data become available. It will be thus necessary to develop robust statistical methods for their analysis. This thesis wants to be a contribution in this exciting field. We first perform this analysis by reviewing the statistical methods used in the original work and by reproducing the most relevant plots using the results obtained through the analysis. In a second stage we present new, original alternative approaches and we apply these methods to analyze the data, comparing the different results obtained.
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Usare il seguente URL per citare questo documento: https://hdl.handle.net/20.500.14240/11066