Quantitative flux coupling analysis

Recon3D enables a three-dimensional view of gene variation in human metabolism

(2018) Elizabeth Brunk et al.   NATURE BIOTECHNOLOGY

fastGapFill: efficient gap filling in metabolic networks

(2014) Ines Thiele et al.   BIOINFORMATICS

A mathematical approach to emergent properties of metabolic networks: Partial coupling relations, hyperarcs and flux ratios

(2014) Sayed-Amir Marashi et al.   JOURNAL OF THEORETICAL BIOLOGY

Fast Reconstruction of Compact Context-Specific Metabolic Network Models

(2014) Nikos Vlassis et al.   PLoS Computational Biology

Time-scale separation - Michaelis and Menten's old idea, still bearing fruit

(2013) Jeremy Gunawardena   FEBS Journal

Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM

(2013) Jonathan M. Dreyfuss et al.   PLoS Computational Biology

F2C2: a fast tool for the computation of flux coupling in genome-scale metabolic networks

(2012) Abdelhalim Larhlimi et al.   BMC BIOINFORMATICS

FFCA: a feasibility-based method for flux coupling analysis of metabolic networks

(2011) Laszlo David et al.   BMC BIOINFORMATICS

The human metabolic reconstruction Recon 1 directs hypotheses of novel human metabolic functions

(2011) Ottar Rolfsson et al.   BMC Systems Biology

Flux coupling analysis of metabolic networks is sensitive to missing reactions

(2010) Sayed-Amir Marashi et al.   BIOSYSTEMS

Systematizing the generation of missing metabolic knowledge

(2010) Jeffrey D. Orth et al.   BIOTECHNOLOGY AND BIOENGINEERING

Computationally efficient flux variability analysis

(2010) Steinn Gudmundsson et al.   BMC BIOINFORMATICS

Computing Knock-Out Strategies in Metabolic Networks

(2008) Utz-Uwe Haus et al.   JOURNAL OF COMPUTATIONAL BIOLOGY

A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

(2008) Markus J Herrgård et al.   NATURE BIOTECHNOLOGY

Co-Regulation of Metabolic Genes Is Better Explained by Flux Coupling Than by Network Distance

(2008) Richard A. Notebaart et al.   PLoS Computational Biology