Automated Model Construction and Genome Annotation for Large-Scale Metabolic Networks
This RTD Project focuses on structural models for metabolic networks, especially their automatic generation and use to annotate genomes and for simulation, in order to arrive at a better understanding of plant metabolism.
Today, metabolic networks are sufficiently well characterized to construct and analyze mathematical models of their behavior at a whole-genome level. This is not due to rich, extensive datasets; existing data is far from comprehensive and even in the best-understood organisms, most kinetic parameters remain undetermined. Whole-network metabolic modeling has largely been enabled by new computational methods that involve the identification and mathematical definition of constraints due to physical laws, environmental conditions, and cellular regulation.
Integrated computational methods
The MetaNetX Technology Development project aims at developing integrated computational methods and tools for the automated reconstruction of genome-scale metabolic networks, including the prediction of novel reactions and pathways and the leverage of this information for refined genome annotation. Our key, novel approach is that overcoming the current technology limitations requires a tight integration of genome annotation methods development, a systematic characterization of potential biochemical reactions, and the development of computational methods for network reconstruction and validation. Primary application examples for this approach are budding yeast and plant (A. thaliana) metabolism.
|Principal Investigator||Prof. Jörg Stelling, Department of Biosystems Science and Engineering (D-BSSE), ETH Zurich|
|Involved Institutions||ETH Zurich, EPF Lausanne, SIB|
|Number of Research Groups||7|
|Project Duration||Aug. 2009 - Jul. 2013|
|Approved SystemsX.ch Funds||CHF 3.980 million|
Updated September 2012