Dr. Daniel Brewer

In his time with CoMPLEX, Daniel worked on a new approach to the biological interpretation and analysis of gene array time series data, focusing on the p53 system. Currently p53 is thought to be the central protein in the DNA damage response and is part of a complex and extensive gene regulatory network. This network integrates a variety of stress signals to produce the up-regulation of active p53 and a range of effects including apoptosis, growth arrest and DNA damage repair. The p53 system has typically been studied qualitatively as a linear pathway, however this approach was insufficient to gain a full functional understanding of the dynamic nature of the network. In this work a better description of the DNA damage response will be constructed through the use of mathematical techniques.

Daniel proposed ordinary differential equations models of the p53 network between DNA damage and p53 up-regulation, including a model that takes into account various localization mechanisms. Parameter estimation was required to validate these models with biological data. Daniel examined a number of established techniques  along with a novel method based on linear algebra, collocation and B-splines. To examine the network downstream of p53 and the global response to DNA damage, a “G” time profile (Gg(t)) quantifying the activity driving the formation of each gene was constructed by Daniel. This was derived from a model of gene transcription, microarray data and mRNA degradation rates.

The new parameter estimation technique developed has been estimated to work significantly better than the other techniques examined. Also, he found that the mechanisms that control the location of p53 significantly contribute to the rapid DNA damage response. The G time profiles suggest that there are four principal transcription activities in the DNA damage response: p53, an early peaking response (possibly AP-1), stopping and restarting the cell cycle, and a double peaked response. The G time profile in combination with a training set of genes can be used to successfully find confirmed p53 targets.

Daniel is currently working as a bioinformatician at the institute of cancer research, UK.

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