Rónán DALY - Data Analysis and Software Manager
Rónán obtained a BAI in computer engineering from the University of Dublin, Trinity College,
an MSc in Artificial Intelligence and a PhD in Machine Learning from the University of Edinburgh.
After this he performed post-doctoral research in the statistical modelling of cell reporter systems and
mass spectrometry data. He has also worked as a lecturer in mathematics and statistics,
and as a software engineer. His interests are in the use of machine learning and Bayesian statistics
applied to complex biological data sets.
Modelling Mass Spectrometry
Rónán has performed research in the use of LC-MS data for the detection of metabolites. He
is particularly interested in the application of sophisticated statistical techniques to model data
obtained from these machines in order to quantify and control the inherent uncertainty and
provide robust identification and quantification.
Analysing Complex Data
Rónán has interests in the application of Bayesian techniques in order to obtain
principled statistical analyses of complex biological data. This also includes the use of
encoded contextual knowledge in order to obtain more powerful conclusions of significance and
provide more robust control of false positives.
- J. Wandy, R. Daly, R. Breitling, and S. Rogers. Incorporating peak grouping information for alignment of multiple liquid chromatography-mass spectrometry datasets. Bioinformatics, 31(12):1999-2006, 2015.
- R. Daly, S. Rogers, J. Wandy, A. Jankevics, K. E. V. Burgess, and R. Breitling. MetAssign: Probabilistic identification of metabolites from LC-MS data using a Bayesian clustering approach. Bioinformatics, 30(19):2764-2771, 2014.
- M. Jiwaji, M. E. Sandison, J. Reboud, R. Stevenson, R. Daly, G. Barkess, K. Faulds, W. Kolch, D. Graham, M. A. Girolami, J. M. Cooper, and A. R. Pitt. Quantification of functionalised gold nanoparticle-targeted knockdown of gene expression in HeLa cells. PLOS ONE, 9(6):e99458, 2014.
- M. Jiwaji, R. Daly, A. Gibriel, G. Barkess, P. McLean, J. Yang, K. Pansare, S. Cumming, A. McLauchlan, P. J. Kamola, M. S. Bhutta, A. G. West, K. L. West, W. Kolch, M. A. Girolami, and A. R. Pitt. Unique reporter-based sensor platforms to monitor signalling in cells. PLOS ONE, 7(11):e50521, 2012.
- R. Daly, K. D. Edwards, J. S. O'Neill, S. Aitken, A. J. Millar, and M. Girolami. Using higher-order dynamic Bayesian networks to model periodic data from the circadian clock of Arabidopsis Thaliana. In V. Kadirkamanathan et al., editors, Proceedings of the Fourth IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2009), volume 5780 of Lecture Notes in Bioinformatics, pages 67-78. Springer, 2009.