I joined CPIB in 2008 as a statistics postdoctoral researcher. I was employed to infer gene regulatory networks from transcriptomics data. Over the past four years, I have predominantly focused on two time course CPIB datasets. The first was over 54 hours and covered the entire period of lateral root development in Arabidopsis. The second was made to investigate the effect of the plant hormone auxin, and involved wildtype and a double mutant arf7arf19 that lacked the two important auxin response factors ARF7 and ARF19.
The lateral root dataset analysis is proceeding well. A principal component analysis of the dataset has revealed circadian clock rhythmicity and we are using this to give direction to our research. In addition, I have used clustering, gene ontology analysis and the online database AraNet to establish networks within the transcriptomics data that have strong links with lateral root development. In parallel with this collaboration with biologists and bioinformaticians, I am developing statistical tools to infer gene networks from the dataset. I have an algorithm that involves clustering, lasso regression, global network parameter selection and reference to AraNet to build large scale networks that are relevant in lateral root development.
Analysis of the second dataset has taken two directions. I used an ensemble of metrics to establish which genes in the genome were putative downstream targets of ARF19. In one of the papers to come from this analysis I carried out a bioinformatics analysis of the performance of these metrics. The other paper was a more technical statistical paper in which the properties of a novel metric were explored with the bioinformatics application used to illustrate the work.
An exciting feature of my time with CPIB that was unanticipated when I was brought into the project is my use of statistical shape analysis to help with predicting and describing shape change in the lateral root primordia of Arabidopsis. For this research I analysed two-dimensional confocal images of lateral root primordia from both wildtype and mutant plants to illustrate how the shape of a lateral root primordium evolves over time, and how this process differs between wildtype and mutant plants. Statistical shape analysis was the topic of my PhD, so it has been a pleasure to put those skills to good use in my employment with CPIB.
Prior to CPIB I worked for a lecturer in the statistics department at the University of Nottingham for a year teaching statistical inference and time series. I obtained my PhD in statistical shape analysis from the University of Nottingham in 2007 under the supervision of Ian Dryden and Huiling Le. During my PhD I focused on using the non-Euclidean geometry of shape space to model shape changes over time and space. The biological examples I used to illustrate my data included the 2D shapes of rat skulls over time and the 3D shapes of lumbar vertebrae of primates. In another section of the PhD I focused on protein molecules and tackled the problem of matching unlabelled point sets corresponding to active sites on the surface of the protein molecules.