Owen Rackham - Post-Doc
Department of Computer Science
University of Bristol
The Merchant Venturers Building, Room 3.16
Woodland Road
Bristol BS8 1UB, United Kingdom

Phone: +44 (0)117 3315173
Fax: +44 (0)117 9545208

Email: owen.rackham@bris.ac.uk
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Background

Hello. I am a post-doctoral research assistant in the computational genomics group, University of Bristol. My research interests span a large number of things including molecular biology, bioinformatics, complexity science, natural computation and artificial intelligence.

I graduated my PhD in 2012 which was titled "understanding and controlling the multiscale complexity of the cell". The adoption of complex systems thinking to Biology has gained momentum over the past decades as scientists have become more aware of the value of considering whole systems rather than individual components. This thesis is an exploration of complexity science tools in the context of modern biology at the cellular level. Three biological systems are introduced and a novel application of complex systems theory applied to them. Firstly, a mathematical modelling approach is applied to the problem of understanding how memories are formed through the process of synaptic plasticity. The approach is shown to be able to accurately predict the behaviour of a synapse, allowing it to be used to inform future experiments. Secondly, a novel statistical approach is applied to the problem of predicting the coiled-coil protein structure based on amino acid sequence alone. The implementation and benchmarking of Spiricoil is described, demonstrating that it outperforms the current leading techniques in the field as well as providing comprehensive evolutionary information about coiled coils to the field for the first time. Finally a network-based predictor is produced with the aim of predicting the correct biological factors required to turn humans cells from one type to another. A system called Mogrify is developed that can integrate gene expression and interaction data in order to produce predictions of re-programming factors that until now would have only been possible through experimentation. Each of these projects represents a considerable contribution to their field and this thesis as a whole provides a model for how complex systems thinking should be used to better understand biological systems.


Research interests

  • Cellular expression, cell fate choice and cell reprogramming
  • Mogrify: predicted factors to facilitate cell conversion.
  • Bioinformatics for regenerative medicine
  • Biological sequence analysis
  • The spiricoil database
  • The FANTOM mouse and human projects
  • Evolution of cell type

Organisations and funding

  • Member: International Society for Computational Biology
  • Member: Japanese Society for the Promotion of Science Alumni Association
  • Member: UK National Stem Cell Network
  • Member: International Society for Stem Cell Research
  • Funding: JSPS Short-term post-doctoral fellowship
  • Funding: Roberts Fund Travel Award
  • Funding: EPSRC Masters scholarship
  • Award: STEM Outreach Department of the Year