Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective.

By C. Schilling, David Letscher, Bernhard O. Palsson. Journal of Theoretical Biology, 2000

706 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e713b3ac7c66673190e18e24d484ab18d662e4d3

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Citations in the corpus

Flux coupling analysis of genome-scale metabolic network reconstructions. (2004, methodology): “Following this spirit, several frameworks for examining structural and topological network properties based on convex analysis have been developed and demonstrated for small-scale metabolic representations (∼100 reactions) to identify extreme pathways (Schilling et al. 2000) or elementary modes (Sch”
Flux balance analysis of biological systems: applications and challenges (2009, methodology): “Methods such as elementary flux mode analysis [47] and extreme pathway analysis [48] have been in vogue for analysing large metabolic networks and have been reviewed elsewhere [49].”
Reconstruction of metabolic networks from genome data and analysis of their global structure for various organisms (2003, methodology): “Several methods such as elementary flux mode analysis and extreme pathway analysis (Schilling et al., 2000; Schilling and Palsson, 2000; Schuster et al., 1999, 2000) have been developed for analyzing the pathway structure of metabolic networks.”
Genome-scale models of microbial cells: evaluating the consequences of constraints (2004, methodology): “These loops have been classified as type III extreme pathways 71 ,and network-based pathway analysis can be used to identify biochemical loops in genome-scale networks 98 .”
Minimal cut sets in biochemical reaction networks (2004, methodology): “Pathway analysis relying on elementary modes or the very closely related extreme pathways (Schuster et al., 2000; Schilling et al., 2000; Klamt and Stelling, 2003a) enables the assessment of structural robustness and redundancy (e.g. Papin et al., 2002; Stelling et al., 2002).”
Using graph theory to analyze biological networks (2011, methodology): “Several methods have also been discovered to analyze the pathway structure of metabolic networks [44-48].”
Evolutionary programming as a platform for in silico metabolic engineering (2005, background): “Because of the large number of reactions occurring in cellular metabolism, the dimensions of the solution space (or the number of feasible metabolic phenotypes) defined by genome-scale models [10,11] is very large.”
Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli (2013, background): “Examples include elementary mode (Schuster et al , 1999) and extreme pathway analyses (Schilling et al , 2000), which have been, for the most part, limited to small-scale networks due to the combinatorial explosion inherent to the methods (Klamt and Stelling, 2002; Yeung et al , 2007).”
Constraint-based models predict metabolic and associated cellular functions (2014, methodology): “In the context of this Review, sets of pathways that are calculated by metabolic network-based pathway analysis tools such as Extreme Pathways and Elementary Flux Modes.”
Thirteen Years of Building Constraint-Based In Silico Models of Escherichia coli (2003, methodology): “Elementary mode analysis (52, 53) and extreme pathway analysis ( 50 ) can be used to characterize vectors in the solution space; the edges of the space correspond to extreme pathways (EP) and are a subset of the elementary modes (EM).”
Modeling and Simulation of Genetic Regulatory Systems: A Literature Review (2002, positive): “…2001), the simulation of the development of the Drosophila embryo in the framework of the Virtual Drosophila project (Kitano et al ., 1997), and the analysis of metabolic networks in E. coli and H. in(cid:143)uenzae (Edwards and Palsson, 2000; Schilling et al ., 2000; Schilling and Palsson, 2000).”