@article{Bornstein08,
    abstract = {{Summary: LibSBML is an application programming interface library for reading, writing, manipulating and validating content expressed in the Systems Biology Markup Language (SBML) format. It is written in ISO C and C++, provides language bindings for Common Lisp, Java, Python, Perl, MATLAB and Octave, and includes many features that facilitate adoption and use of both SBML and the li-brary. Developers can embed libSBML in their applications, saving themselves the work of implementing their own SBML parsing, ma-nipulation, and validation software. Availability: LibSBML 3 was released in August 2007. Source code, binaries and documentation are freely available under LGPL open-source terms from http://sbml.org/software/libsbml. Contact: sbml-team@caltech.edu 10.1093/bioinformatics/btn051}},
    author = {Bornstein, Benjamin J. and Keating, Sarah M. and Jouraku, Akiya and Hucka, Michael},
    citeulike-article-id = {2342470},
    citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/btn051},
    citeulike-linkout-1 = {http://bioinformatics.oxfordjournals.org/content/24/6/880.abstract},
    citeulike-linkout-2 = {http://bioinformatics.oxfordjournals.org/content/24/6/880.full.pdf},
    citeulike-linkout-3 = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/24/6/880},
    citeulike-linkout-4 = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2517632/},
    citeulike-linkout-5 = {http://view.ncbi.nlm.nih.gov/pubmed/18252737},
    citeulike-linkout-6 = {http://www.hubmed.org/display.cgi?uids=18252737},
    day = {15},
    doi = {10.1093/bioinformatics/btn051},
    issn = {1367-4811},
    journal = {Bioinformatics (Oxford, England)},
    keywords = {sbml, software, standards, systems-biology},
    month = mar,
    number = {6},
    pages = {880--881},
    pmcid = {PMC2517632},
    pmid = {18252737},
    posted-at = {2008-04-23 19:22:28},
    priority = {2},
    publisher = {Oxford University Press},
    title = {{LibSBML: an API library for SBML.}},
    url = {http://dx.doi.org/10.1093/bioinformatics/btn051},
    volume = {24},
    year = {2008}
}

@article{DenMeersche09,
  abstract = {Functions that (1.) Find the minimum/maximum of a linear or quadratic function: min or max (f(x)), where f(x) = ||Ax-b||^2 or f(x) = sum(ai*xi) subject to equality constraints Ex=f and/or inequality constraints Gx>=h. (2.) Sample an underdetermined- or overdetermined system Ex=f subject to Gx>=h, and if applicable Ax~=b. (3.) Solve a linear system Ax=B for the unknown x. Includes banded and tridiagonal linear systems. The package calls Fortran functions from LINPACK},
  accepted = {2009-03-31},
  added-at = {2012-02-11T00:26:20.000+0100},
  author = {den Meersche, Karel Van and Soetaert, Karline and Oevelen, Dick Van},
  bibdate = {2009-03-31},
  biburl = {http://www.bibsonomy.org/bibtex/2d1696d45fe5d99782c48f3d37af0fe81/peter.ralph},
  coden = {JSSOBK},
  day = 27,
  interhash = {efd26310682037318fa16c88a6dd48fe},
  intrahash = {d1696d45fe5d99782c48f3d37af0fe81},
  issn = {1548-7660},
  journal = {Journal of Statistical Software, Code Snippets},
  keywords = {R ill-posed_problems inverse_problems mcmc statistics},
  month = {4},
  number = 1,
  pages = {1--15},
  submitted = {2008-05-26},
  timestamp = {2012-02-11T00:26:20.000+0100},
  title = {{\tt xsample()}: An {R} Function for Sampling Linear Inverse Problems},
  url = {http://www.jstatsoft.org/v30/c01},
  volume = 30,
  year = 2009
}

@article{Dusick2007,
abstract = {Patients with traumatic brain injury (TBI) routinely exhibit cerebral glucose uptake in excess of that expected by the low levels of oxygen consumption and lactate production. This brings into question the metabolic fate of glucose. Prior studies have shown increased flux through the pentose phosphate cycle (PPC) during cellular stress. This study assessed the PPC after TBI in humans. [1,2-(13)C(2)]glucose was infused for 60 mins in six consented, severe-TBI patients (GCS<9) and six control subjects. Arterial and jugular bulb blood sampled during infusion was analyzed for (13)C-labeled isotopomers of lactate by gas chromatography/mass spectroscopy. The product of lactate concentration and fractional abundance of isotopomers was used to determine blood concentration of each isotopomer. The difference of jugular and arterial concentrations determined cerebral contribution. The formula PPC=(m1/m2)/(3+(m1/m2)) was used to calculate PPC flux relative to glycolysis. There was enrichment of [1,2-(13)C(2)]glucose in arterial-venous blood (enrichment averaged 16.6\% in TBI subjects and 28.2\% in controls) and incorporation of (13)C-label into lactate, showing metabolism of labeled substrate. The PPC was increased in TBI patients relative to controls (19.6 versus 6.9\%, respectively; P=0.002) and was excellent for distinguishing the groups (AUC=0.944, P<0.0001). No correlations were found between PPC and other clinical parameters, although PPC was highest in patients studied within 48 h of injury (averaging 33\% versus 13\% in others; P=0.0006). This elevation in the PPC in the acute period after severe TBI likely represents a shunting of substrate into alternative biochemical pathways that may be critical for preventing secondary injury and initiating recovery.},
author = {Dusick, Joshua R and Glenn, Thomas C and Lee, W N Paul and Vespa, Paul M and Kelly, Daniel F and Lee, Stefan M and Hovda, David A and Martin, Neil A},
doi = {10.1038/sj.jcbfm.9600458},
file = {::},
isbn = {0271-678X},
issn = {0271-678X},
journal = {Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism},
pages = {1593--1602},
pmid = {17293841},
title = {{Increased pentose phosphate pathway flux after clinical traumatic brain injury: a [1,2-13C2]glucose labeling study in humans.}},
volume = {27},
year = {2007}
}

@manual{Lawrence2013,
author = {Lawrence, Michael},
title = {{rsbml: R support for SBML, using libsbml}},
url = {http://www.sbml.org},
year = {2013},
Note = {R package version 2.12.0. \textit{Package available at  \url{http://www.bioconductor.org/packages/release/bioc/html/rsbml.html}}}
}

@article{Lying-Tunell1980,
abstract = {The cerebral blood flow (CBF) and cerebral metabolic rate (CMR) of oxygen, glucose, lactate, pyruvate, ketone bodies, and 24 amino acids were examined in 10 healthy subjects, five 21-24 and five 55-65 years old. The subjects were free from drugs. The results of psychometric and neurological examinations were negative. CBF was determined with the nitrous oxide method on the subjects who were awake and normocapnic and had fasted overnight. No differences were found between the young and the old groups except in arterial levels of four amino acids, viz. aspartic acid, methionine, lysine, and tryptophan. In the whole group of 10 subjects, a significant cerebral net uptake (expressed as median values in mumol X kg-1 X min-1) was found not only for oxygen (1719) and glucose (248), but also for acetoacetate (4.3), D-beta-hydroxybutyrate (6.2), arginine (2.0), leucine (5.2), and isoleucine (1.2). There was a significant net release of lactate (-28). CBF was positively correlated to the CMR of oxygen and D-beta-hydroxybutyrate. Arterial concentrations and CMR were positively correlated for ketone bodies, glutamic acid, proline and taurine. It is of particular interest that the whole group of healthy subjects showed a significant cerebral uptake of branched-chain and dibasic amino acids.},
author = {Lying-Tunell, U and Lindblad, B S and Malmlund, H O and Persson, B},
issn = {0001-6314},
journal = {Acta neurologica Scandinavica},
keywords = {Adult,Aged,Amino Acids,Amino Acids: metabolism,Brain,Brain: metabolism,Cerebrovascular Circulation,Glucose,Glucose: metabolism,Humans,Ketone Bodies,Ketone Bodies: metabolism,Lactates,Lactates: metabolism,Middle Aged,Oxygen Consumption,Pyruvates,Pyruvates: metabolism},
month = nov,
number = {5},
pages = {265--75},
pmid = {7468149},
title = {{Cerebral blood flow and metabolic rate of oxygen, glucose, lactate, pyruvate, ketone bodies and amino acids.}},                                                                                                                                                      
url = {http://www.ncbi.nlm.nih.gov/pubmed/7468149},                                                                                                                                                                                                                            
volume = {62},                                                                                                                                                                                                                                                                 
year = {1980}                                                                                                                                                                                                                                                                  
}                                       

@Manual{GentryXXXX,
title = {Rgraphviz: Provides plotting capabilities for R graph objects},
author = {Jeff Gentry and Li Long and Robert Gentleman and {Seth} and Florian Hahne and Deepayan Sarkar and Kasper Hansen},
Note = {R package version 1.32.0. \textit{Package available at \url{http://www.bioconductor.org/packages/release/bioc/html/Rgraphviz.html}}}
}

@Manual{MurrellXXXX,
title = {hyperdraw: Visualizing Hypergaphs},
author = {Paul Murrell},    
Note = {R package version 1.6.0. \textit{Package available at \url{http://www.bioconductor.org/packages/release/bioc/html/hyperdraw.html}}}
}

@article{Oevelen2009,
author = {Oevelen, Dick and Meersche, Karel and Meysman, Filip J. R. and Soetaert, Karline and Middelburg, Jack J. and V\'{e}zina, Alain F.},
doi = {10.1007/s10021-009-9297-6},
file = {:home/hettling/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Oevelen et al. - 2009 - Quantifying Food Web Flows Using Linear Inverse Models.pdf:pdf},
issn = {1432-9840},
journal = {Ecosystems},
month = nov,
number = {1},
pages = {32--45},
title = {{Quantifying Food Web Flows Using Linear Inverse Models}},
url = {http://link.springer.com/10.1007/s10021-009-9297-6},
volume = {13},
year = {2009}
}

@article{Patel2005,
abstract = {Previous studies have shown that the glutamate/glutamine (Glu/Gln) neurotransmitter cycle and neuronal glucose oxidation are proportional (1:1), with increasing neuronal activity above isoelectricity. GABA, a product of Glu metabolism, is synthesized from astroglial Gln and contributes to total Glu/Gln neurotransmitter cycling, although the fraction contributed by GABA is unknown. In the present study, we used (13)C NMR spectroscopy together with i.v. infusions of [1,6-(13)C(2)]glucose and [2-(13)C]acetate to separately determine rates of Glu/Gln and GABA/Gln cycling and their respective tricarboxylic acid cycles in the rat cortex under conditions of halothane anesthesia and pentobarbital-induced isoelectricity. Under 1\% halothane anesthesia, GABA/Gln cycle flux comprised 23\% of total (Glu plus GABA) neurotransmitter cycling and 18\% of total neuronal tricarboxylic acid cycle flux. In isoelectric cortex, glucose oxidation was reduced >3-fold in glutamatergic and GABAergic neurons, and neurotransmitter cycling was below detection. Hence, in both cell types, the primary energetic costs are associated with neurotransmission, which increase together as cortical activity is increased. The contribution of GABAergic neurons and inhibition to cortical energy metabolism has broad implications for the interpretation of functional imaging signals.},
author = {Patel, Anant B and de Graaf, Robin a and Mason, Graeme F and Rothman, Douglas L and Shulman, Robert G and Behar, Kevin L},
doi = {10.1073/pnas.0501703102},
file = {::},
issn = {0027-8424},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
keywords = {Acetates,Acetates: administration \& dosage,Acetates: blood,Acetates: metabolism,Acetates: pharmacology,Amino Acids,Amino Acids: metabolism,Anesthetics,Animals,Biological Transport,Biological Transport: drug effects,Blood Glucose,Blood Glucose: analysis,Cerebral Cortex,Cerebral Cortex: cytology,Cerebral Cortex: drug effects,Cerebral Cortex: metabolism,Energy Metabolism,Energy Metabolism: drug effects,Energy Metabolism: physiology,GABA Modulators,GABA Modulators: pharmacology,Glucose,Glucose: administration \& dosage,Glucose: pharmacology,Glutamic Acid,Glutamic Acid: metabolism,Glutamine,Glutamine: metabolism,Halothane,Halothane: pharmacology,Inhalation,Inhalation: pharmacology,Magnetic Resonance Spectroscopy,Male,Neuroglia,Neuroglia: drug effects,Neuroglia: metabolism,Neurons,Neurons: drug effects,Neurons: metabolism,Oxidation-Reduction,Pentobarbital,Pentobarbital: pharmacology,Rats,Sprague-Dawley,gamma-Aminobutyric Acid,gamma-Aminobutyric Acid: biosynthesis,gamma-Aminobutyric Acid: metabolism},
month = apr,
number = {15},
pages = {5588--93},
pmid = {15809416},
title = {{The contribution of GABA to glutamate/glutamine cycling and energy metabolism in the rat cortex in vivo}},
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=556230\&tool=pmcentrez\&rendertype=abstract},
volume = {102},
year = {2005}
}

@article{Schellenberger2010,
abstract = {ABSTRACT: BACKGROUND: Genome-scale metabolic reconstructions under the Constraint Based Reconstruction and Analysis (COBRA) framework are valuable tools for analyzing the metabolic capabilities of organisms and interpreting experimental data. As the number of such reconstructions and analysis methods increases, there is a greater need for data uniformity and ease of distribution and use. Description We describe BiGG, a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest. CONCLUSIONS: BiGG addresses a need in the systems biology community to have access to high quality curated metabolic models and reconstructions. It is freely available for academic use at http://bigg.ucsd.edu.},
author = {Schellenberger, Jan and Park, Junyoung O and Conrad, Tom M and Palsson, Bernhard O},
doi = {10.1186/1471-2105-11-213},
issn = {1471-2105},
journal = {BMC Bioinformatics},
keywords = {Genome,Genomics,Genomics: methods,Knowledge Bases,Metabolic Networks and Pathways,Software},
month = apr,
number = {1},
pages = {213},
pmid = {20426874},
title = {{BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions.}},
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2874806\&tool=pmcentrez\&rendertype=abstract},
volume = {11},
year = {2010},
Note = {\textit{Database available at \url{http://bigg.ucsd.edu}}}
}

@article{Schellenberger2011,
abstract = {Over the past decade, a growing community of researchers has emerged around the use of constraint-based reconstruction and analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a substantial update of this in silico toolbox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include (i) network gap filling, (ii) (13)C analysis, (iii) metabolic engineering, (iv) omics-guided analysis and (v) visualization. As with the first version, the COBRA Toolbox reads and writes systems biology markup language-formatted models. In version 2.0, we improved performance, usability and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the toolbox and validate results. This toolbox lowers the barrier of entry to use powerful COBRA methods.},
author = {Schellenberger, Jan and Que, Richard and Fleming, Ronan M T and Thiele, Ines and Orth, Jeffrey D and Feist, Adam M and Zielinski, Daniel C and Bordbar, Aarash and Lewis, Nathan E and Rahmanian, Sorena and Kang, Joseph and Hyduke, Daniel R and Palsson, Bernhard \O},
doi = {10.1038/nprot.2011.308},
file = {:home/hettling/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Schellenberger et al. - 2011 - Quantitative prediction of cellular metabolism with constraint-based models the COBRA Toolbox v2.0.pdf:pdf},
issn = {1750-2799},
journal = {Nature Protocols},
keywords = {Algorithms,Computational Biology,Computational Biology: methods,Metabolic Networks and Pathways,Software},
month = sep,
number = {9},
pages = {1290--307},
pmid = {21886097},
publisher = {Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
shorttitle = {Nat. Protocols},
title = {{Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0.}},
url = {http://dx.doi.org/10.1038/nprot.2011.308},
volume = {6},
year = {2011},
Note = {\textit{Software available at \url{http://opencobra.sourceforge.net}}}                                                           }}
}

@article{Thiele2013,
abstract = {Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ∼2× more reactions and ∼1.7× more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77\% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.},
author = {Thiele, Ines and Swainston, Neil and Fleming, Ronan M T and Hoppe, Andreas and Sahoo, Swagatika and Aurich, Maike K and Haraldsdottir, Hulda and Mo, Monica L and Rolfsson, Ottar and Stobbe, Miranda D and Thorleifsson, Stefan G and Agren, Rasmus and B\"{o}lling, Christian and Bordel, Sergio and Chavali, Arvind K and Dobson, Paul and Dunn, Warwick B and Endler, Lukas and Hala, David and Hucka, Michael and Hull, Duncan and Jameson, Daniel and Jamshidi, Neema and Jonsson, Jon J and Juty, Nick and Keating, Sarah and Nookaew, Intawat and {Le Nov\`{e}re}, Nicolas and Malys, Naglis and Mazein, Alexander and Papin, Jason A and Price, Nathan D and Selkov, Evgeni and Sigurdsson, Martin I and Simeonidis, Evangelos and Sonnenschein, Nikolaus and Smallbone, Kieran and Sorokin, Anatoly and van Beek, Johannes H G M and Weichart, Dieter and Goryanin, Igor and Nielsen, Jens and Westerhoff, Hans V and Kell, Douglas B and Mendes, Pedro and Palsson, Bernhard \O},
doi = {10.1038/nbt.2488},
issn = {1546-1696},
journal = {Nature Biotechnology},
month = may,
number = {5},
pages = {419--25},
pmid = {23455439},
publisher = {Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
shorttitle = {Nat Biotech},
title = {{A community-driven global reconstruction of human metabolism.}},
url = {http://dx.doi.org/10.1038/nbt.2488},
volume = {31},
year = {2013},
Note = {\textit{Database available at \url{http://humanmetabolism.org}}}
}

@article{VanBeek2011,
abstract = {The human physiological system is stressed to its limits during endurance sports competition events. We describe a whole body computational model for energy conversion during bicycle racing. About 23 per cent of the metabolic energy is used for muscle work, the rest is converted to heat. We calculated heat transfer by conduction and blood flow inside the body, and heat transfer from the skin by radiation, convection and sweat evaporation, resulting in temperature changes in 25 body compartments. We simulated a mountain time trial to Alpe d'Huez during the Tour de France. To approach the time realized by Lance Armstrong in 2004, very high oxygen uptake must be sustained by the simulated cyclist. Temperature was predicted to reach 39\{degrees\}C in the brain, and 39.7\{degrees\}C in leg muscle. In addition to the macroscopic simulation, we analysed the buffering of bursts of high adenosine triphosphate hydrolysis by creatine kinase during cyclical muscle activity at the biochemical pathway level. To investigate the low oxygen to carbohydrate ratio for the brain, which takes up lactate during exercise, we calculated the flux distribution in cerebral energy metabolism. Computational modelling of the human body, describing heat exchange and energy metabolism, makes simulation of endurance sports events feasible.},
author = {van Beek, J. H. G. M. and Supandi, F. and Gavai, A. K. and de Graaf, A. A. and Binsl, T. W. and Hettling, H.},
doi = {10.1098/rsta.2011.0166},
file = {::},
issn = {1364-503X},
journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
month = oct,
number = {1954},
pages = {4295--4315},                                                                                                                                                                                                                                                          
title = {{Simulating the physiology of athletes during endurance sports events: modelling human energy conversion and metabolism}},                                                                                                                                            
url = {http://rsta.royalsocietypublishing.org/cgi/content/abstract/369/1954/4295},                                                                                                                                                                                             
volume = {369},                                                                                                                                                                                                                                                                
year = {2011}                                                                                                                                                                                                                                                                  
}                                          