references.bib

@article{Breiman2001,
  author    = {Leo Breiman},
  title     = {Random Forests},
  journal   = {Machine Learning},
  volume    = {45},
  number    = {1},
  pages     = {5--32},
  year      = {2001},
  url       = {https://doi.org/10.1023/A:1010933404324},
  doi       = {10.1023/A:1010933404324},
  timestamp = {Wed, 14 Nov 2018 00:00:00 +0100},
  biburl    = {https://dblp.org/rec/bib/journals/ml/Breiman01},
}

@inproceedings{Louppe2013,
 author = {Louppe, Gilles and Wehenkel, Louis and Sutera, Antonio and Geurts, Pierre},
 title = {Understanding Variable Importances in Forests of Randomized Trees},
 booktitle = {Proceedings of the 26th International Conference on Neural Information Processing Systems - Volume 1},
 series = {NIPS'13},
 year = {2013},
 location = {Lake Tahoe, Nevada},
 pages = {431--439},
 numpages = {9},
 url = {http://dl.acm.org/citation.cfm?id=2999611.2999660},
 acmid = {2999660},
 publisher = {Curran Associates Inc.},
 address = {USA},
}

@ARTICLE{Beaulieu-Jones2017-tg,
  title    = "Reproducibility of computational workflows is automated using
              continuous analysis",
  author   = "Beaulieu-Jones, Brett K and Greene, Casey S",
  abstract = "Replication, validation and extension of experiments are crucial
              for scientific progress. Computational experiments are scriptable
              and should be easy to reproduce. However, computational analyses
              are designed and run in a specific computing environment, which
              may be difficult or impossible to match using written
              instructions. We report the development of continuous analysis, a
              workflow that enables reproducible computational analyses.
              Continuous analysis combines Docker, a container technology akin
              to virtual machines, with continuous integration, a software
              development technique, to automatically rerun a computational
              analysis whenever updates or improvements are made to source code
              or data. This enables researchers to reproduce results without
              contacting the study authors. Continuous analysis allows
              reviewers, editors or readers to verify reproducibility without
              manually downloading and rerunning code and can provide an audit
              trail for analyses of data that cannot be shared.",
  journal  = "Nat. Biotechnol.",
  volume   =  35,
  number   =  4,
  pages    = "342--346",
  month    =  apr,
  year     =  2017,
  language = "en"
}

@ARTICLE{Heirendt2017-ra,
  title         = "Creation and analysis of biochemical constraint-based
                   models: the {COBRA} Toolbox v3.0",
  author        = "Heirendt, Laurent and Arreckx, Sylvain and Pfau, Thomas and
                   Mendoza, Sebasti{\'a}n N and Richelle, Anne and Heinken,
                   Almut and Haraldsd{\'o}ttir, Hulda S and Wachowiak, Jacek
                   and Keating, Sarah M and Vlasov, Vanja and Magnusd{\'o}ttir,
                   Stefania and Ng, Chiam Yu and Preciat, German and {\v
                   Z}agare, Alise and Chan, Siu H J and Aurich, Maike K and
                   Clancy, Catherine M and Modamio, Jennifer and Sauls, John T
                   and Noronha, Alberto and Bordbar, Aarash and Cousins,
                   Benjamin and El Assal, Diana C and Valcarcel, Luis V and
                   Apaolaza, I{\~n}igo and Ghaderi, Susan and Ahookhosh, Masoud
                   and Ben Guebila, Marouen and Kostromins, Andrejs and
                   Sompairac, Nicolas and Le, Hoai M and Ma, Ding and Sun,
                   Yuekai and Wang, Lin and Yurkovich, James T and Oliveira,
                   Miguel A P and Vuong, Phan T and El Assal, Lemmer P and
                   Kuperstein, Inna and Zinovyev, Andrei and Scott Hinton, H
                   and Bryant, William A and Arag{\'o}n Artacho, Francisco J
                   and Planes, Francisco J and Stalidzans, Egils and Maass,
                   Alejandro and Vempala, Santosh and Hucka, Michael and
                   Saunders, Michael A and Maranas, Costas D and Lewis, Nathan
                   E and Sauter, Thomas and Palsson, Bernhard {\O} and Thiele,
                   Ines and Fleming, Ronan M T",
  abstract      = "COnstraint-Based Reconstruction and Analysis (COBRA)
                   provides a molecular mechanistic framework for integrative
                   analysis of experimental data and quantitative prediction of
                   physicochemically and biochemically feasible phenotypic
                   states. The COBRA Toolbox is a comprehensive software suite
                   of interoperable COBRA methods. It has found widespread
                   applications in biology, biomedicine, and biotechnology
                   because its functions can be flexibly combined to implement
                   tailored COBRA protocols for any biochemical network.
                   Version 3.0 includes new methods for quality controlled
                   reconstruction, modelling, topological analysis, strain and
                   experimental design, network visualisation as well as
                   network integration of chemoinformatic, metabolomic,
                   transcriptomic, proteomic, and thermochemical data. New
                   multi-lingual code integration also enables an expansion in
                   COBRA application scope via high-precision,
                   high-performance, and nonlinear numerical optimisation
                   solvers for multi-scale, multi-cellular and reaction kinetic
                   modelling, respectively. This protocol can be adapted for
                   the generation and analysis of a constraint-based model in a
                   wide variety of molecular systems biology scenarios. This
                   protocol is an update to the COBRA Toolbox 1.0 and 2.0. The
                   COBRA Toolbox 3.0 provides an unparalleled depth of
                   constraint-based reconstruction and analysis methods.",
  month         =  oct,
  year          =  2017,
  archivePrefix = "arXiv",
  primaryClass  = "q-bio.QM",
  eprint        = "1710.04038"
}

@ARTICLE{Ebrahim2013-wf,
  title    = "{COBRApy}: {COnstraints-Based} Reconstruction and Analysis for
              Python",
  author   = "Ebrahim, Ali and Lerman, Joshua A and Palsson, Bernhard O and
              Hyduke, Daniel R",
  abstract = "BACKGROUND: COnstraint-Based Reconstruction and Analysis (COBRA)
              methods are widely used for genome-scale modeling of metabolic
              networks in both prokaryotes and eukaryotes. Due to the successes
              with metabolism, there is an increasing effort to apply COBRA
              methods to reconstruct and analyze integrated models of cellular
              processes. The COBRA Toolbox for MATLAB is a leading software
              package for genome-scale analysis of metabolism; however, it was
              not designed to elegantly capture the complexity inherent in
              integrated biological networks and lacks an integration framework
              for the multiomics data used in systems biology. The openCOBRA
              Project is a community effort to promote constraints-based
              research through the distribution of freely available software.
              RESULTS: Here, we describe COBRA for Python (COBRApy), a Python
              package that provides support for basic COBRA methods. COBRApy is
              designed in an object-oriented fashion that facilitates the
              representation of the complex biological processes of metabolism
              and gene expression. COBRApy does not require MATLAB to function;
              however, it includes an interface to the COBRA Toolbox for MATLAB
              to facilitate use of legacy codes. For improved performance,
              COBRApy includes parallel processing support for computationally
              intensive processes. CONCLUSION: COBRApy is an object-oriented
              framework designed to meet the computational challenges
              associated with the next generation of stoichiometric
              constraint-based models and high-density omics data sets.
              AVAILABILITY: http://opencobra.sourceforge.net/",
  journal  = "BMC Syst. Biol.",
  volume   =  7,
  pages    = "74",
  month    =  aug,
  year     =  2013,
  language = "en"
}

@ARTICLE{Heavner2015-gq,
  title    = "Transparency in metabolic network reconstruction enables scalable
              biological discovery",
  author   = "Heavner, Benjamin D and Price, Nathan D",
  abstract = "Reconstructing metabolic pathways has long been a focus of active
              research. Now, draft models can be generated from genomic
              annotation and used to simulate metabolic fluxes of mass and
              energy at the whole-cell scale. This approach has led to an
              explosion in the number of functional metabolic network models.
              However, more models have not led to expanded coverage of
              metabolic reactions known to occur in the biosphere. Thus, there
              exists opportunity to reconsider the process of reconstruction
              and model derivation to better support the less-scalable
              investigative processes of biocuration and experimentation.
              Realizing this opportunity to improve our knowledge of metabolism
              requires developing new tools that make reconstructions more
              useful by highlighting metabolic network knowledge limitations to
              guide future research.",
  journal  = "Curr. Opin. Biotechnol.",
  volume   =  34,
  pages    = "105--109",
  month    =  aug,
  year     =  2015,
  language = "en"
}

@article{Magnsdttir2016,
  doi = {10.1038/nbt.3703},
  url = {https://doi.org/10.1038/nbt.3703},
  year = {2016},
  month = nov,
  publisher = {Springer Science and Business Media {LLC}},
  volume = {35},
  number = {1},
  pages = {81--89},
  author = {Stefan{\'{\i}}a Magn{\'{u}}sd{\'{o}}ttir and Almut Heinken and Laura Kutt and Dmitry A Ravcheev and Eugen Bauer and Alberto Noronha and Kacy Greenhalgh and Christian J\"{a}ger and Joanna Baginska and Paul Wilmes and Ronan M T Fleming and Ines Thiele},
  title = {Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota},
  journal = {Nature Biotechnology}
}

@article{Babaei2018,
  doi = {10.1038/nbt.4213},
  url = {https://doi.org/10.1038/nbt.4213},
  year = {2018},
  month = aug,
  publisher = {Springer Science and Business Media {LLC}},
  volume = {36},
  number = {8},
  pages = {682--686},
  author = {Parizad Babaei and Saeed Shoaie and Boyang Ji and Jens Nielsen},
  title = {Challenges in modeling the human gut microbiome},
  journal = {Nature Biotechnology}
}

@article{Magnsdttir2018,
  doi = {10.1038/nbt.4212},
  url = {https://doi.org/10.1038/nbt.4212},
  year = {2018},
  month = aug,
  publisher = {Springer Science and Business Media {LLC}},
  volume = {36},
  number = {8},
  pages = {686--691},
  author = {Stefan{\'{\i}}a Magn{\'{u}}sd{\'{o}}ttir and Almut Heinken and Ronan M T Fleming and Ines Thiele},
  title = {Reply to "Challenges in modeling the human gut microbiome"},
  journal = {Nature Biotechnology}
}

@article{Bchel2013,
  doi = {10.1186/1752-0509-7-116},
  url = {https://doi.org/10.1186/1752-0509-7-116},
  year = {2013},
  publisher = {Springer Science and Business Media {LLC}},
  volume = {7},
  number = {1},
  pages = {116},
  author = {Finja B\"{u}chel and Nicolas Rodriguez and Neil Swainston and Clemens Wrzodek and Tobias Czauderna and Roland Keller and Florian Mittag and Michael Schubert and Mihai Glont and Martin Golebiewski and Martijn van Iersel and Sarah Keating and Matthias Rall and Michael Wybrow and Henning Hermjakob and Michael Hucka and Douglas B Kell and Wolfgang M\"{u}ller and Pedro Mendes and Andreas Zell and Claudine Chaouiya and Julio Saez-Rodriguez and Falk Schreiber and Camille Laibe and Andreas Dr\"{a}ger and Nicolas Le Nov{\`{e}}re},
  title = {Path2Models: large-scale generation of computational models from biochemical pathway maps},
  journal = {{BMC} Systems Biology}
}

@article{Li2010,
  doi = {10.1186/1752-0509-4-92},
  url = {https://doi.org/10.1186/1752-0509-4-92},
  year = {2010},
  publisher = {Springer Nature},
  volume = {4},
  number = {1},
  pages = {92},
  author = {Chen Li and Marco Donizelli and Nicolas Rodriguez and Harish Dharuri and Lukas Endler and Vijayalakshmi Chelliah and Lu Li and Enuo He and Arnaud Henry and Melanie I Stefan and Jacky L Snoep and Michael Hucka and Nicolas Le Nov{\`{e}}re and Camille Laibe},
  title = {{BioModels} Database: An enhanced,  curated and annotated resource for published quantitative kinetic models},
  journal = {{BMC} Systems Biology}
}

@article{LeNovere2006,
  doi = {10.1093/nar/gkj092},
  url = {https://doi.org/10.1093/nar/gkj092},
  year = {2006},
  month = jan,
  publisher = {Oxford University Press ({OUP})},
  volume = {34},
  number = {90001},
  pages = {D689--D691},
  author = {N. Le Novere},
  title = {{BioModels} Database: a free,  centralized database of curated,  published,  quantitative kinetic models of biochemical and cellular systems},
  journal = {Nucleic Acids Research}
}

@article{Chelliah2014,
  doi = {10.1093/nar/gku1181},
  url = {https://doi.org/10.1093/nar/gku1181},
  year = {2014},
  month = nov,
  publisher = {Oxford University Press ({OUP})},
  volume = {43},
  number = {D1},
  pages = {D542--D548},
  author = {Vijayalakshmi Chelliah and Nick Juty and Ishan Ajmera and Raza Ali and Marine Dumousseau and Mihai Glont and Michael Hucka and Gaël Jalowicki and Sarah Keating and Vincent Knight-Schrijver and Audald Lloret-Villas and Kedar Nath Natarajan and Jean-Baptiste Pettit and Nicolas Rodriguez and Michael Schubert and Sarala M. Wimalaratne and Yangyang Zhao and Henning Hermjakob and Nicolas Le~Nov{\`{e}}re and Camille Laibe},
  title = {{BioModels}: ten-year anniversary},
  journal = {Nucleic Acids Research}
}

@article{Machado2018,
  doi = {10.1093/nar/gky537},
  url = {https://doi.org/10.1093/nar/gky537},
  year = {2018},
  month = jun,
  publisher = {Oxford University Press ({OUP})},
  volume = {46},
  number = {15},
  pages = {7542--7553},
  author = {Daniel Machado and Sergej Andrejev and Melanie Tramontano and Kiran Raosaheb Patil},
  title = {Fast automated reconstruction of genome-scale metabolic models for microbial species and communities},
  journal = {Nucleic Acids Research}
}

@article{Arkin2018,
  doi = {10.1038/nbt.4163},
  url = {https://doi.org/10.1038/nbt.4163},
  year = {2018},
  month = jul,
  publisher = {Springer Science and Business Media {LLC}},
  volume = {36},
  number = {7},
  pages = {566--569},
  author = {Adam P Arkin and Robert W Cottingham and Christopher S Henry and Nomi L Harris and Rick L Stevens and Sergei Maslov and Paramvir Dehal and Doreen Ware and Fernando Perez and Shane Canon and Michael W Sneddon and Matthew L Henderson and William J Riehl and Dan Murphy-Olson and Stephen Y Chan and Roy T Kamimura and Sunita Kumari and Meghan M Drake and Thomas S Brettin and Elizabeth M Glass and Dylan Chivian and Dan Gunter and David J Weston and Benjamin H Allen and Jason Baumohl and Aaron A Best and Ben Bowen and Steven E Brenner and Christopher C Bun and John-Marc Chandonia and Jer-Ming Chia and Ric Colasanti and Neal Conrad and James J Davis and Brian H Davison and Matthew DeJongh and Scott Devoid and Emily Dietrich and Inna Dubchak and Janaka N Edirisinghe and Gang Fang and Jos{\'{e}} P Faria and Paul M Frybarger and Wolfgang Gerlach and Mark Gerstein and Annette Greiner and James Gurtowski and Holly L Haun and Fei He and Rashmi Jain and Marcin P Joachimiak and Kevin P Keegan and Shinnosuke Kondo and Vivek Kumar and Miriam L Land and Folker Meyer and Marissa Mills and Pavel S Novichkov and Taeyun Oh and Gary J Olsen and Robert Olson and Bruce Parrello and Shiran Pasternak and Erik Pearson and Sarah S Poon and Gavin A Price and Srividya Ramakrishnan and Priya Ranjan and Pamela C Ronald and Michael C Schatz and Samuel M D Seaver and Maulik Shukla and Roman A Sutormin and Mustafa H Syed and James Thomason and Nathan L Tintle and Daifeng Wang and Fangfang Xia and Hyunseung Yoo and Shinjae Yoo and Dantong Yu},
  title = {{KBase}: The United States Department of Energy Systems Biology Knowledgebase},
  journal = {Nature Biotechnology}
}

@article{Rocha2010,
  doi = {10.1186/1752-0509-4-45},
  url = {https://doi.org/10.1186/1752-0509-4-45},
  year = {2010},
  month = apr,
  publisher = {Springer Nature},
  volume = {4},
  number = {1},
  author = {Isabel Rocha and Paulo Maia and Pedro Evangelista and Paulo Vila{\c{c}}a and Sim{\~{a}}o Soares and Jos{\'{e}} P Pinto and Jens Nielsen and Kiran R Patil and Eug{\'{e}}nio C Ferreira and Miguel Rocha},
  title = {{OptFlux}: an open-source software platform for in silico metabolic engineering},
  journal = {{BMC} Systems Biology}
}

@article{Ebrahim2015,
  doi = {10.15252/msb.20156157},
  url = {https://doi.org/10.15252/msb.20156157},
  year = {2015},
  month = oct,
  publisher = {{EMBO}},
  volume = {11},
  number = {10},
  pages = {831},
  author = {Ali Ebrahim and Eivind Almaas and Eugen Bauer and Aarash Bordbar and Anthony P Burgard and Roger L Chang and Andreas Dr\"{a}ger and Iman Famili and Adam M Feist and Ronan MT Fleming and Stephen S Fong and Vassily Hatzimanikatis and Markus J Herrg{\aa}rd and Allen Holder and Michael Hucka and Daniel Hyduke and Neema Jamshidi and Sang Yup Lee and Nicolas Le Nov{\`{e}}re and Joshua A Lerman and Nathan E Lewis and Ding Ma and Radhakrishnan Mahadevan and Costas Maranas and Harish Nagarajan and Ali Navid and Jens Nielsen and Lars K Nielsen and Juan Nogales and Alberto Noronha and Csaba Pal and Bernhard O Palsson and Jason A Papin and Kiran R Patil and Nathan D Price and Jennifer L Reed and Michael Saunders and Ryan S Senger and Nikolaus Sonnenschein and Yuekai Sun and Ines Thiele},
  title = {Do genome-scale models need exact solvers or clearer standards?},
  journal = {Molecular Systems Biology}
}

@article{King2015,
  doi = {10.1093/nar/gkv1049},
  url = {https://doi.org/10.1093/nar/gkv1049},
  year = {2015},
  month = oct,
  publisher = {Oxford University Press ({OUP})},
  volume = {44},
  number = {D1},
  pages = {D515--D522},
  author = {Zachary A. King and Justin Lu and Andreas Dr\"{a}ger and Philip Miller and Stephen Federowicz and Joshua A. Lerman and Ali Ebrahim and Bernhard O. Palsson and Nathan E. Lewis},
  title = {{BiGG} Models: A platform for integrating,  standardizing and sharing genome-scale models},
  journal = {Nucleic Acids Research}
}

@article{Karp2009,
  doi = {10.1093/bib/bbp043},
  url = {https://doi.org/10.1093/bib/bbp043},
  year = {2009},
  month = dec,
  publisher = {Oxford University Press ({OUP})},
  volume = {11},
  number = {1},
  pages = {40--79},
  author = {P. D. Karp and S. M. Paley and M. Krummenacker and M. Latendresse and J. M. Dale and T. J. Lee and P. Kaipa and F. Gilham and A. Spaulding and L. Popescu and T. Altman and I. Paulsen and I. M. Keseler and R. Caspi},
  title = {Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology},
  journal = {Briefings in Bioinformatics}
}

@article{Aite2018,
  doi = {10.1371/journal.pcbi.1006146},
  url = {https://doi.org/10.1371/journal.pcbi.1006146},
  year = {2018},
  month = may,
  publisher = {Public Library of Science ({PLoS})},
  volume = {14},
  number = {5},
  pages = {e1006146},
  author = {M{\'{e}}ziane Aite and Marie Chevallier and Cl{\'{e}}mence Frioux and Camille Trottier and Jeanne Got and Mar{\'{\i}}a Paz Cort{\'{e}}s and Sebasti{\'{a}}n N. Mendoza and Gr{\'{e}}gory Carrier and Olivier Dameron and Nicolas Guillaudeux and Mauricio Latorre and Nicol{\'{a}}s Loira and Gabriel V. Markov and Alejandro Maass and Anne Siegel},
  editor = {Jens Nielsen},
  title = {Traceability,  reproducibility and wiki-exploration for {\textquotedblleft}{\`{a}}-la-carte{\textquotedblright} reconstructions of genome-scale metabolic models},
  journal = {{PLOS} Computational Biology}
}

@article{Thorleifsson2011,
  doi = {10.1093/bioinformatics/btr308},
  url = {https://doi.org/10.1093/bioinformatics/btr308},
  year = {2011},
  month = may,
  publisher = {Oxford University Press ({OUP})},
  volume = {27},
  number = {14},
  pages = {2009--2010},
  author = {S. G. Thorleifsson and I. Thiele},
  title = {{rBioNet}: A {COBRA} toolbox extension for reconstructing high-quality biochemical networks},
  journal = {Bioinformatics}
}

@article{Gilbert2019,
  doi = {10.1093/bioinformatics/btz088},
  url = {https://doi.org/10.1093/bioinformatics/btz088},
  year = {2019},
  month = feb,
  publisher = {Oxford University Press ({OUP})},
  volume = {35},
  number = {18},
  pages = {3397--3403},
  author = {James Gilbert and Nicole Pearcy and Rupert Norman and Thomas Millat and Klaus Winzer and John King and Charlie Hodgman and Nigel Minton and Jamie Twycross},
  editor = {Russell Schwartz},
  title = {Gsmodutils: a python based framework for test-driven genome scale metabolic model development},
  journal = {Bioinformatics}
}

@article{Hackett2016,
  doi = {10.1126/science.aaf2786},
  url = {https://doi.org/10.1126/science.aaf2786},
  year = {2016},
  month = oct,
  publisher = {American Association for the Advancement of Science ({AAAS})},
  volume = {354},
  number = {6311},
  pages = {aaf2786--aaf2786},
  author = {S. R. Hackett and V. R. T. Zanotelli and W. Xu and J. Goya and J. O. Park and D. H. Perlman and P. A. Gibney and D. Botstein and J. D. Storey and J. D. Rabinowitz},
  title = {Systems-level analysis of mechanisms regulating yeast metabolic flux},
  journal = {Science}
}

@article{Bergmann2014,
  doi = {10.1186/s12859-014-0369-z},
  url = {https://doi.org/10.1186/s12859-014-0369-z},
  year = {2014},
  month = dec,
  publisher = {Springer Science and Business Media {LLC}},
  volume = {15},
  number = {1},
  author = {Frank T Bergmann and Richard Adams and Stuart Moodie and Jonathan Cooper and Mihai Glont and Martin Golebiewski and Michael Hucka and Camille Laibe and Andrew K Miller and David P Nickerson and Brett G Olivier and Nicolas Rodriguez and Herbert M Sauro and Martin Scharm and Stian Soiland-Reyes and Dagmar Waltemath and Florent Yvon and Nicolas Le Nov{\`{e}}re},
  title = {{COMBINE} archive and {OMEX} format: one file to share all information to reproduce a modeling project},
  journal = {{BMC} Bioinformatics}
}

@article{Waltemath2011,
  doi = {10.1186/1752-0509-5-198},
  url = {https://doi.org/10.1186/1752-0509-5-198},
  year = {2011},
  publisher = {Springer Nature},
  volume = {5},
  number = {1},
  pages = {198},
  author = {Dagmar Waltemath and Richard Adams and Frank T Bergmann and Michael Hucka and Fedor Kolpakov and Andrew K Miller and Ion I Moraru and David Nickerson and Sven Sahle and Jacky L Snoep and Nicolas Le Nov{\`{e}}re},
  title = {Reproducible computational biology experiments with {SED}-{ML} - The Simulation Experiment Description Markup Language},
  journal = {{BMC} Systems Biology}
}

@article{OBrien2013,
  doi = {10.1038/msb.2013.52},
  url = {https://doi.org/10.1038/msb.2013.52},
  year = {2013},
  month = jan,
  publisher = {{EMBO}},
  volume = {9},
  number = {1},
  pages = {693},
  author = {Edward J OBrien and Joshua A Lerman and Roger L Chang and Daniel R Hyduke and Bernhard {\O} Palsson},
  title = {Genome-scale models of metabolism and gene expression extend and refine growth phenotype prediction},
  journal = {Molecular Systems Biology}
}

@article{Vasilakou2016,
  doi = {10.1016/j.mib.2016.07.008},
  url = {https://doi.org/10.1016/j.mib.2016.07.008},
  year = {2016},
  month = oct,
  publisher = {Elsevier {BV}},
  volume = {33},
  pages = {97--104},
  author = {Eleni Vasilakou and Daniel Machado and Axel Theorell and Isabel Rocha and Katharina N\"{o}h and Marco Oldiges and S Aljoscha Wahl},
  title = {Current state and challenges for dynamic metabolic modeling},
  journal = {Current Opinion in Microbiology}
}

@article{Thiel2017,
  doi = {10.1371/journal.pcbi.1005280},
  url = {https://doi.org/10.1371/journal.pcbi.1005280},
  year = {2017},
  month = feb,
  publisher = {Public Library of Science ({PLoS})},
  volume = {13},
  number = {2},
  pages = {e1005280},
  author = {Christoph Thiel and Henrik Cordes and Lorenzo Fabbri and H{\'{e}}l{\`{e}}ne Eloise Aschmann and Vanessa Baier and Ines Smit and Francis Atkinson and Lars Mathias Blank and Lars Kuepfer},
  editor = {Donna K. Slonim},
  title = {A Comparative Analysis of Drug-Induced Hepatotoxicity in Clinically Relevant Situations},
  journal = {{PLOS} Computational Biology}
}

@article{Agren2013,
  doi = {10.1371/journal.pcbi.1002980},
  url = {https://doi.org/10.1371/journal.pcbi.1002980},
  year = {2013},
  month = mar,
  publisher = {Public Library of Science ({PLoS})},
  volume = {9},
  number = {3},
  pages = {e1002980},
  author = {Rasmus Agren and Liming Liu and Saeed Shoaie and Wanwipa Vongsangnak and Intawat Nookaew and Jens Nielsen},
  editor = {Costas D. Maranas},
  title = {The {RAVEN} Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum},
  journal = {{PLoS} Computational Biology}
}

@article{Caspi2009,
  doi = {10.1093/nar/gkp875},
  url = {https://doi.org/10.1093/nar/gkp875},
  year = {2009},
  month = oct,
  publisher = {Oxford University Press ({OUP})},
  volume = {38},
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