Metabolic network structure determines key aspects of functionality and regulation

By Jörg Stelling, Steffen Klamt, Katja Bettenbrock, S. Schuster, Ernst Dieter Gilles. Nature, 2002

844 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d8010b17a83afbf6995ddd89a656a525e8a64d7e

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Citations in the corpus

Robustness of Cellular Functions (2004, neutral): “Despite the system’s apparent simplicity, it shows of metabolic networks (Almaas et al., 2004; Covert et al., 2004; Stelling et al., 2002) become tractable through features of advanced biological regulation such as high sensitivity to environmental changes over a broad dy- their large-scale in silic”
Structural and functional analysis of cellular networks with CellNetAnalyzer (2007, neutral): “coli (studied in [9]), and Figure 4 displays a SFN model of signalling pathways involved in T-cell activation (a larger version of this model is studied in [10]).”
Maize Metabolic Network Construction and Transcriptome Analysis (2013, neutral): “Several metabolic network reconstructions are currently available (Stelling et al., 2002; Papp et al., 2004; Vastrik et al., 2007; Tsesmetzis et al., 2008; Ferrer, 2009; Latendresse et al., 2011).”
Functional topology in a network of protein interactions (2004, background): “Complex biological and artificial networks show graph properties that relate to the function these networks carry (Milo et al., 2002; Yook et al., 2002; Tu, 2000; Williams et al., 2002; Eckmann and Moses, 2002; Girvan and Newman, 2002; Stelling et al., 2002).”
Minimal cut sets in biochemical reaction networks (2004, methodology): “Size distribution of the MCSs in the central metabolism of E.coli for four different substrates. has been claimed by Stelling et al. (2002): growth on glucose is structurally less fragile (more robust) than growth on acetate.”
GENEVESTIGATOR. Arabidopsis Microarray Database and Analysis Toolbox1[w] (2004, background): “…exploitation of large-scale gene expression data-sets, mainly from Saccharomyces cerevisiae and Escherichia coli , has already led to the discovery of global structures governing metabolic and regulatory networks (Lee et al., 2002; Ravasz et al., 2002; Stelling et al., 2002; Ihmels et al., 2004).”
Comparative Genomics in Eukaryotes (2005, background): “, 2001) or the topology of the metabolic network (Forster et al., 2003; Stelling et al., 2002).”
Graph theory and networks in Biology. (2006, methodology): “An alternative approach to using detailed metabolic models for the prediction of gene deletion phenotypes relies on the notion of elementary flux modes [133].”
Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease (2011, background): “regulation (24, 25), modularity (26, 27), essentiality and mutant viability (28), genetic and environmental robustness (29), adaptation (30, 31), and species interaction (32).”
Cleaning up with genomics: applying molecular biology to bioremediation (2003, background): “Such descriptions are becoming possible owing to important advances in the development of in silico models of cell metabolis”
Genome-scale models of bacterial metabolism: reconstruction and applications (2008, background): “Conversely, the relative importance of reactions in metabolism was scored using elementary routes, reactions involved in many routes being likely to be key players in metabolism (Stelling et al ., 2002).”
A methodology for the structural and functional analysis of signaling and regulatory networks (2006, methodology): “The minimal hitting sets of the target paths and hence the MCSs of our deletion task would be: {C}, {B, E}, {I2, B}, {I1, E} and {I1, I2}.”
Network science of biological systems at different scales: A review. (2017, background): “[29] Stelling J, Klamt S, Bettenbrock K, Schuster S, Gilles E.”