报告内容摘要

Implicit in the collection of high-throughput data is an assumption that computational models ultimately will facilitate biological discovery, reconciliation of heterogeneous data types, identify inconsistencies and enable the systematic generation of hypotheses. Current na?ve statistically models falls well short of this ambition, while the use of the conventional dynamic models of physics suffers from our inability to accurately determine in vivo parameters. Constraint based models use stoichiometry, thermodynamics, physical capacity constraints and regulation to define feasible solution spaces, which can then be explored using a range tools to infer network behaviour. The framework has proven surprisingly powerful in its ability to predict the behaviour of natural as well as engineered networks in microbes.
Higher eukaryotes present additional challenges in the form of (a) compartmentalised metabolism with difficult to identify intracellular transporters and pathway duplication, (b) complex genome regulation, (b) multicellularity and associated difficulty in defining objectives, and (d) difficulty of reliable manipulation and analysis at cellular level. However, the same challenges that make higher eukaryotic systems less tractable also makes the potential advantage of model based analysis far greater. In this presentation, I will discuss a range of mathematical and experimental approaches we use to identify and constrain the degrees of freedom in animal and plant genome scale models to make them more tractable. The aim is to - at a minimum - make explicit the assumptions made in more practical, reduced models and - ideally - develop controls for these assumptions.

报告人简介

Professor Nielsen heads the Systems and Synthetic Biology Group at the Australian Institute for Bioengineering and Nanotechnology. Using thermodynamic principles, novel approaches are developed for the rational design of complex pathways as well as handling complex, transient dynamics in developing tissue. A team of 40 people use these novel approaches in the design of bioprocesses as diverse as the production of blood cells for transfusion and the production of industrial biopolymers. Professor Nielsen also heads the Metabolomics Australia Queensland Node, which is focused on assisting Australian scientists developing flux modeling and analysis approaches for their biological systems of interest

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Email: lars.nielsen@uq.edu.au