Science jobs from University College Dublin: job description
NB: this position is restricted to European Union candidates (EU status is based largely on recent residency – www.ucd.ie/registry/adminservices/fees/eu_fees.htm#2)
Are you interested in interdisciplinary research in mathematics, computing and biology?
New high-throughput technologies in biology have opened up exciting opportunities for numerate scientists to work in advanced areas of biological research. Our programme takes students from a variety of backgrounds (statistics, engineering, mathematics, computer science, biology, chemistry, physics) and gives them a structured training during their PhD, tailored to their needs. Each project is jointly run by two supervisors, one with a background in modelling or computational analysis and one with an experimental research programme. The student is integrated into the research teams of both research groups.
Applications are invited from EU students for 4-year PhD positions under the graduate education programme (GREP) of the Irish Research Council for Science, Engineering and Technology (IRCSET). Most studentships commence Oct 2009 Understanding design principles of regulatory and metabolic networks
Supervisors: Zoltan Neufeld UCD (Systems Biology), Denis Shields, UCD
Biochemical reactions between different types of molecules (proteins, metabolites, genes etc.) form a complex network of interactions composed of metabolic and regulatory pathways. Although the reaction dynamics of metabolic networks can be described by a system of kinetic equations this is of limited use since the parameters and the functional forms of reaction fluxes and parts of the regulatory interactions are largely unknown. New approaches have been proposed that instead of analysing the full reaction dynamics focus on the constraints arising from the structure of the stoichiometric matrix that describes the network of interactions between the components. Taking into account these constraints, flux balance analysis (FBA) can determine the flux distribution corresponding to an optimal state of the system (e.g. corresponding to maximal growth rate). Such approaches have been validated experimentally and can also be used to predict effects of genetic knockouts.
The PhD project will aim to understand the mechanism of dynamic regulatory processes through which the optimal metabolic states are reached and maintained in biological systems. First synthetic metabolic network models will be used with full reaction dynamics to design “genetic” regulatory schemes that by adjusting reaction fluxes can drive the system to the optimal metabolic state for the given network. Understanding the characteristic features of the regulatory interactions in the synthetic metabolic networks will then be used to formulate hypotheses than can be tested on real biological systems (e.g. using data available on metabolic and genetic interactions in microbial systems). In a later stage the work will be extended to study adaptation in response to changes or fluctuations in the external environment (e.g. due to variable sources of nutrients) by designing signaling interactions that can optimise the systems behavior under such conditions. Finally robustness and evolvability of the regulation with respect to genetic mutations will also be considered.
The project will involve mathematical and computational modeling and analysis of biological data and is most suitable for a student with strong quantitative mathematical background and some knowledge and/or interest in biology.
References
Price et al. Genome-scale models of microbial cells: evaluating the consequences of constraints. Nat Rev Microbiol (2004) vol. 2 pp. 886
Covert et al. Integrating high-throughput and computational data elucidates bacterial networks. Nature (2004) vol. 429 pp. 92-96
Ibarra et al. Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature (2002) vol. 420 (6912) pp. 186-189
Prill et al. Dynamic Properties of Network Motifs Contribute to Biological Network Organization. Plos Biol (2005) vol. 3 (11) pp. e343
Min Lee et al. Dynamic Analysis of Integrated Signaling, Metabolic, and Regulatory Networks. PLoS Comput Biol (2008) vol. 4 (5) pp. e1000086
Application procedure procedure and further details
http://bioinformatics.ucd.ie/PhD/apply_09.html
This studentship is funded by IRCSET (www.ircset.ie). Funds are available for a student stipend (€16,000), fees, some lab consumables ( up to €5,000 per year), and a travel budget to allow the student to get work experience abroad and industrial work experience in a company in Ireland or abroad.
Contact Details: bioinfo@ucd.ie
Closing date: 30th March 2009
University College Dublin
Website:
http://bioinformatics.ucd.ie/…
Location:
Conway Institute, UCD, Dublin
Expires:
May 15, 2009
