A community-driven global reconstruction of human metabolism
Open accessAbstract
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/.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A community-driven reconstruction, Recon 2, was released in 2013 and included 65 cell type-specific models.
“A community-driven reconstruction, Recon 2, was released in 2013 and included 65 cell type–specific models (309).”
From Metabolic Flexibility as an Adaptation to Energy Resources and Requirements in Health and Disease (2018) · cites this paper as [309]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
What is flux balance analysis?
Orth, J. D., Thiele, I., & Palsson, B. Ø. (2010) · Nature Biotechnology · doi:10.1038/nbt.1614 · Cited by 3,903 · see citing works
Self-citationHucka, M., Finney, A., Sauro, H. M., Bolouri, H., Doyle, J. C., Kitano, H., Arkin, A. P., Bornstein, B. J., Bray, D., Cornish-Bowden, A., et al. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg015 · Cited by 3,060 · see citing works
Self-citationDrugBank: a knowledgebase for drugs, drug actions and drug targets
Wishart, D. S., Knox, C., Guo, A. C., Cheng, D., Shrivastava, S., Tzur, D., Gautam, B., & Hassanali, M. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm958 · Cited by 2,852 · see citing works
Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites
Wikoff, W. R., Anfora, A. T., Liu, J., Schultz, P. G., Lesley, S. A., Peters, E. C., & Siuzdak, G. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0812874106 · Cited by 2,677 · see citing works
Towards a knowledge-based Human Protein Atlas
Uhlen, M., Oksvold, P., Fagerberg, L., Lundberg, E., Jonasson, K., Forsberg, M., Zwahlen, M., Kampf, C., Wester, K., Hober, S., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt1210-1248 · Cited by 2,440 · see citing works
HMDB: a knowledgebase for the human metabolome
Wishart, D. S., Knox, C., Guo, A. C., Eisner, R., Young, N., Gautam, B., Hau, D., Psychogios, N., Dong, E., Bouatra, S., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn810 · Cited by 1,874 · see citing works
Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
Schellenberger, J., Que, R., Fleming, R. M. T., Thiele, I., Orth, J. D., Feist, A. M., Zielinski, D. C., Bordbar, A., Lewis, N. E., Rahmanian, S., et al. (2011) · Nature Protocols · doi:10.1038/nprot.2011.308 · Cited by 1,835 · see citing works
Self-citationA protocol for generating a high-quality genome-scale metabolic reconstruction
Thiele, I., & Palsson, B. Ø. (2010) · Nature Protocols · doi:10.1038/nprot.2009.203 · Cited by 1,789 · see citing works
Self-citationMetabolite profiling identifies a key role for glycine in rapid cancer cell proliferation
Jain, M., Nilsson, R., Sharma, S., Madhusudhan, N., Kitami, T., Souza, A. L., Kafri, R., Kirschner, M. W., Clish, C. B., & Mootha, V. K. (2012) · Science · doi:10.1126/science.1218595 · Cited by 1,403 · see citing works
Global reconstruction of the human metabolic network based on genomic and bibliomic data
Duarte, N. C., Becker, S. A., Jamshidi, N., Thiele, I., Mo, M. L., Vo, T. D., Srivas, R., & Palsson, B. Ø. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0610772104 · Cited by 1,374 · see citing works
Self-citationApplications of genome‐scale metabolic reconstructions
Oberhardt, M., Palsson, B. Ø., & Papin, J. A. (2009) · Molecular Systems Biology · doi:10.1038/msb.2009.77 · Cited by 820 · see citing works
Self-citationZelena, E., Dunn, W. B., Broadhurst, D., Francis‐McIntyre, S., Carroll, K. M., Begley, P., O’Hagan, S., Knowles, J. D., Halsall, A., HUSERMET Consortium, et al. (2009) · Analytical Chemistry · doi:10.1021/ac8019366 · Cited by 815 · see citing works
Self-citationSystems biology properties of reconstructed networks
Palsson, B. Ø. (2006) · Cited by 684 · see citing works
Self-citationNetwork-based prediction of human tissue-specific metabolism
Shlomi, T., Cabili, M. N., Herrgård, M. J., Palsson, B. Ø., & Ruppin, E. (2008) · Nature Biotechnology · doi:10.1038/nbt.1487 · Cited by 637 · see citing works
Self-citationMinimum information requested in the annotation of biochemical models (MIRIAM)
Novère, N. L., Finney, A., Hucka, M., Bhalla, U. S., Campagne, F., Collado-Vides, J., Crampin, E. J., Halstead, M., Klipp, E., Mendes, P., et al. (2005) · Nature Biotechnology · doi:10.1038/nbt1156 · Cited by 622 · see citing works
Self-citationSystems Biology: Properties of Reconstructed Networks
Palsson, B. Ø. (2006) · doi:10.1017/cbo9780511790515 · Cited by 617 · see citing works
Self-citationHerrgård, M. J., Swainston, N., Dobson, P., Dunn, W. B., Arga, K. Y., Arvas, M., Blüthgen, N., Borger, S., Costenoble, R., Heinemann, M., et al. (2008) · Nature Biotechnology · doi:10.1038/nbt1492 · Cited by 588 · see citing works
Self-citationHaem oxygenase is synthetically lethal with the tumour suppressor fumarate hydratase
Frezza, C., Zheng, L., Folger, O., Rajagopalan, K. N., MacKenzie, E. D., Jerby, L., Micaroni, M., Chaneton, B., Adam, J., Hedley, A., et al. (2011) · Nature · doi:10.1038/nature10363 · Cited by 503 · see citing works
Predicting selective drug targets in cancer through metabolic networks
Folger, O., Jerby‐Arnon, L., Frezza, C., Gottlieb, E., Ruppin, E., & Shlomi, T. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.35 · Cited by 469 · see citing works
Ågren, R., Bordel, S., Mardinoğlu, A., Pornputtapong, N., Nookaew, I., & Nielsen, J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002518 · Cited by 430 · see citing works
Self-citationMetabolic footprinting and systems biology: the medium is the message
Kell, D. B., Brown, M., Davey, H. M., Dunn, W. B., Spasić, ., & Oliver, S. G. (2005) · Nature Reviews Microbiology · doi:10.1038/nrmicro1177 · Cited by 423 · see citing works
Self-citationJerby‐Arnon, L., Shlomi, T., & Ruppin, E. (2010) · Molecular Systems Biology · doi:10.1038/msb.2010.56 · Cited by 365 · see citing works
Computationally efficient flux variability analysis
Guðmundsson, S., & Thiele, I. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-489 · Cited by 360 · see citing works
Self-citationMcHugh, D. M. S., Cameron, C. A., Abdenur, J. E., Abdulrahman, M., Adair, O. O., Nuaimi, S. A. A., Åhlman, H., Allen, J. J., Antonozzi, I., Archer, S., et al. (2011) · Genetics in Medicine · doi:10.1097/gim.0b013e31820d5e67 · Cited by 348 · see citing works
Systemic multicompartmental effects of the gut microbiome on mouse metabolic phenotypes
Claus, S. P., Tsang, T. M., Wang, Y., Cloarec, O., Skordi, E., Martin, F., Rezzi, S., Ross, A., Kochhar, S., Holmes, E., et al. (2008) · Molecular Systems Biology · doi:10.1038/msb.2008.56 · Cited by 334 · see citing works
Systems approach to refining genome annotation
Reed, J. L., Patel, T., Chen, K. H., Joyce, A. R., Applebee, M. K., Herring, C. D., Bui, O., Knight, E. M., Fong, S. S., & Palsson, B. Ø. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0603364103 · Cited by 283 · see citing works
Self-citationGille, C., Bölling, C., Hoppe, A., Bulik, S., Hoffmann, S., Hübner, K., Karlstaedt, A., Ganeshan, R., König, M., Rother, K. M., et al. (2010) · Molecular Systems Biology · doi:10.1038/msb.2010.62 · Cited by 280 · see citing works
Self-citationIntegration of expression data in genome-scale metabolic network reconstructions
Blazier, A. S., & Papin, J. A. (2012) · Frontiers in Physiology · doi:10.3389/fphys.2012.00299 · Cited by 259 · see citing works
Self-citationBordbar, A., Lewis, N. E., Schellenberger, J., Palsson, B. Ø., & Jamshidi, N. (2010) · Molecular Systems Biology · doi:10.1038/msb.2010.68 · Cited by 252 · see citing works
Self-citationA genome-wide association study of metabolic traits in human urine
Suhre, K., Wallaschofski, H., Raffler, J., Friedrich, N., Haring, R., Michael, K., Wasner, C., Krebs, A., Kronenberg, F., Chang, D., et al. (2011) · Nature Genetics · doi:10.1038/ng.837 · Cited by 246 · see citing works
Systems-level characterization of a host-microbe metabolic symbiosis in the mammalian gut
Heinken, A., Sahoo, S., Fleming, R. M. T., & Thiele, I. (2013) · Gut Microbes · doi:10.4161/gmic.22370 · Cited by 219 · see citing works
Self-citationChang, R. L., Xie, L., Xie, L., Bourne, P. E., & Palsson, B. Ø. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000938 · Cited by 204 · see citing works
Self-citationTowards a genome-scale kinetic model of cellular metabolism
B, K. S. A., Simeonidis, E., Swainston, N., & Mendes, P. (2010) · BMC Systems Biology · doi:10.1186/1752-0509-4-6 · Cited by 171 · see citing works
Self-citationPredicting metabolic biomarkers of human inborn errors of metabolism
Shlomi, T., Cabili, M. N., & Ruppin, E. (2009) · Molecular Systems Biology · doi:10.1038/msb.2009.22 · Cited by 171 · see citing works
A detailed genome-wide reconstruction of mouse metabolism based on human Recon 1
Sigurdsson, M. I., Jamshidi, N., Steingrimsson, E., Thiele, I., & Palsson, B. Ø. (2010) · BMC Systems Biology · doi:10.1186/1752-0509-4-140 · Cited by 154 · see citing works
Self-citationYeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network
Heavner, B., B, K. S. A., Barker, B., Mendes, P., & Walker, L. P. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-55 · Cited by 142 · see citing works
Self-citationThiele, I., Hyduke, D. R., Steeb, B., Fankam, G., Allen, D. K., Bazzani, S., Charusanti, P., Chen, F., Fleming, R. M. T., Hsiung, C. A., et al. (2011) · BMC Systems Biology · doi:10.1186/1752-0509-5-8 · Cited by 141 · see citing works
Self-citationUsing the reconstructed genome-scale human metabolic network to study physiology and pathology
Bordbar, A., & Palsson, B. O. (2012) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2011.02494.x · Cited by 115 · see citing works
Self-citationCompartmentalization of the Edinburgh Human Metabolic Network
Hao, T., Ma, H., Zhao, X., & Goryanin, I. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-393 · Cited by 100 · see citing works
Self-citationSomething from nothing − bridging the gap between constraint‐based and kinetic modelling
B, K. S. A., Simeonidis, E., Broomhead, D. S., & Kell, D. B. (2007) · FEBS Journal · doi:10.1111/j.1742-4658.2007.06076.x · Cited by 98 · see citing works
Self-citationThe SuBliMinaL Toolbox: automating steps in the reconstruction of metabolic networks
Swainston, N., B, K. S. A., Mendes, P., Kell, D. B., & Paton, N. W. (2011) · Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics · doi:10.1515/jib-2011-186 · Cited by 97 · see citing works
Self-citationPaglia, G., Hrafnsdóttir, S., Magnúsdóttir, M., Fleming, R. M. T., Thorlacius, S., Palsson, B. Ø., & Thiele, I. (2011) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-011-5556-4 · Cited by 77 · see citing works
Self-citationThe human metabolic reconstruction Recon 1 directs hypotheses of novel human metabolic functions
Rolfsson, Ó., Palsson, B. Ø., & Thiele, I. (2011) · BMC Systems Biology · doi:10.1186/1752-0509-5-155 · Cited by 74 · see citing works
Self-citationCritical assessment of human metabolic pathway databases: a stepping stone for future integration
Stobbe, M. D., Houten, S. M., Jansen, G. A., van Kampen, A. H. C., & Moerland, P. D. (2011) · BMC Systems Biology · doi:10.1186/1752-0509-5-165 · Cited by 72 · see citing works
Self-citationFASIMU: flexible software for flux-balance computation series in large metabolic networks
Hoppe, A., Hoffmann, S., Gerasch, A., Gille, C., & Holzhütter, H. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-28 · Cited by 72 · see citing works
Self-citationA compendium of inborn errors of metabolism mapped onto the human metabolic network
Sahoo, S., Franzson, L., Jónsson, J. J., & Thiele, I. (2012) · Molecular BioSystems · doi:10.1039/c2mb25075f · Cited by 71 · see citing works
Self-citationPredicting the impact of diet and enzymopathies on human small intestinal epithelial cells
Sahoo, S., & Thiele, I. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt119 · Cited by 67 · see citing works
Self-citationReconstruction annotation jamborees: a community approach to systems biology
Thiele, I., & Palsson, B. Ø. (2010) · Molecular Systems Biology · doi:10.1038/msb.2010.15 · Cited by 65 · see citing works
Self-citationrBioNet: A COBRA toolbox extension for reconstructing high-quality biochemical networks
Thorleifsson, S. G., & Thiele, I. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr308 · Cited by 63 · see citing works
Self-citationHaraldsdóttir, H. S., Thiele, I., & Fleming, R. M. T. (2012) · Biophysical Journal · doi:10.1016/j.bpj.2012.02.032 · Cited by 53 · see citing works
Self-citationThe SuBliMinaL Toolbox: automating steps in the reconstruction of metabolic networks
Swainston, N., Smallbone, K., Mendes, P., et al. (2011) · PubMed · doi:10.2390/biecoll-jib-2011-186 · Cited by 46 · see citing works
Self-citationlibAnnotationSBML: a library for exploiting SBML annotations
Swainston, N., & Mendes, P. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp392 · Cited by 29 · see citing works
Self-citationRolfsson, Ó., Paglia, G., Magnúsdóttir, M., Palsson, B. Ø., & Thiele, I. (2012) · Biochemical Journal · doi:10.1042/bj20120980 · Cited by 25 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Metabolomics: beyond biomarkers and towards mechanisms
Johnson, C. H., Ivanisevic, J., & Siuzdak, G. (2016) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2016.25 · Cited by 2,829 · see citing works
Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0
Heirendt, L., Arreckx, S., Pfau, T., Mendoza, S. N., Richelle, A., Heinken, A., Haraldsdóttir, H. S., Wachowiak, J., Keating, S., Vlasov, V., et al. (2019) · Nature Protocols · doi:10.1038/s41596-018-0098-2 · Cited by 1,253 · see citing works
Self-citationThe whole-genome landscape of medulloblastoma subtypes
Northcott, P. A., Buchhalter, I., Morrissy, A. S., Hovestadt, V., Weischenfeldt, J., Ehrenberger, T., Gröbner, S., Segura-Wang, M., Zichner, T., Rudneva, V. A., et al. (2017) · Nature · doi:10.1038/nature22973 · Cited by 1,112 · see citing works
ChEBI in 2016: Improved services and an expanding collection of metabolites
Hastings, J., Owen, G., Dekker, A., Ennis, M., Kale, N., Muthukrishnan, V., Turner, S., Swainston, N., Mendes, P., & Steinbeck, C. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1031 · Cited by 1,083 · see citing works
Self-citationConstraint-based models predict metabolic and associated cellular functions
Bordbar, A., Monk, J. M., King, Z. A., & Palsson, B. Ø. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3643 · Cited by 818 · see citing works
Self-citationAn Integrated Metabolic Atlas of Clear Cell Renal Cell Carcinoma
Hakimi, A. A., Reznik, E., Lee, C., Creighton, C. J., Brannon, A. R., Luna, A., Aksoy, B. A., Liu, E. M., Shen, R., Lee, W., et al. (2016) · Cancer Cell · doi:10.1016/j.ccell.2015.12.004 · Cited by 791 · see citing works
Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota
Magnúsdóttir, S., Heinken, A., Kutt, L., Ravcheev, D. A., Bauer, E., Noronha, A., Greenhalgh, K., Jäger, C., Baginska, J., Wilmes, P., et al. (2017) · Nature Biotechnology · doi:10.1038/nbt.3703 · Cited by 798 · see citing works
Self-citationCurrent status and applications of genome-scale metabolic models
Gu, C., Kim, G. B., Kim, W. J., Kim, H. U., & Lee, S. Y. (2019) · Genome biology · doi:10.1186/s13059-019-1730-3 · Cited by 765 · see citing works
Metabolic Flexibility as an Adaptation to Energy Resources and Requirements in Health and Disease
Smith, R. L., Soeters, M. R., Wüst, R. C. I., & Houtkooper, R. H. (2018) · Endocrine Reviews · doi:10.1210/er.2017-00211 · Cited by 787 · see citing works
Recon3D enables a three-dimensional view of gene variation in human metabolism
Brunk, E., Sahoo, S., Zielinski, D. C., Altunkaya, A., Dräger, A., Mih, N., Gatto, F., Nilsson, A., Preciat, G., Aurich, M. K., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4072 · Cited by 755 · see citing works
Self-citationUsing Genome-scale Models to Predict Biological Capabilities
O’Brien, E. J., Monk, J. M., & Palsson, B. Ø. (2015) · Cell · doi:10.1016/j.cell.2015.05.019 · Cited by 709 · see citing works
Self-citationSystems biology and multi-omics integration: viewpoints from the metabolomics research community
Pinu, F. R., Beale, D. J., Paten, A. M., Kouremenos, K., Swarup, S., Schirra, H. J., & Wishart, D. (2019) · Metabolites · doi:10.3390/metabo9040076 · Cited by 723 · see citing works
Deep learning improves prediction of drug–drug and drug–food interactions
Ryu, J. Y., Kim, H. U., & Lee, S. Y. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1803294115 · Cited by 662 · see citing works
Dietary methionine influences therapy in mouse cancer models and alters human metabolism
Gao, X., Sanderson, S. M., Dai, Z., Reid, M. A., Cooper, D. E., Lu, M., Richie, J. P., Ciccarella, A., Calcagnotto, A., Mikhael, P. G., et al. (2019) · Nature · doi:10.1038/s41586-019-1437-3 · Cited by 657 · see citing works
Hosios, A. M., Hecht, V. C., Danai, L. V., Johnson, M. O., Rathmell, J. C., Steinhauser, M. L., Manalis, S. R., & Vander Heiden, M. G. (2016) · Developmental Cell · doi:10.1016/j.devcel.2016.02.012 · Cited by 641 · see citing works
Metabolomics enables precision medicine: “A White Paper, Community Perspective”
for “Precision Medicine and Pharmacometabolomics Task Group”-Metabolomics Society Initiative, Beger, R. D., Dunn, W., Schmidt, M. A., Gross, S. S., Kirwan, J. A., Cascante, M., Brennan, L., Wishart, D. S., Oresic, M., et al. (2016) · Metabolomics · doi:10.1007/s11306-016-1094-6 · Cited by 592 · see citing works
Self-citationA Call for Systematic Research on Solute Carriers
César‐Razquin, A., Snijder, B., Frappier‐Brinton, T., Isserlin, R., Gyimesi, G., Bai, X., Reithmeier, R. A., Hepworth, D., Hediger, M. A., Edwards, A. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.07.022 · Cited by 581 · see citing works
What do drug transporters really do?
Nigám, S. K. (2014) · Nature Reviews Drug Discovery · doi:10.1038/nrd4461 · Cited by 531 · see citing works
Big Data Analytics in Healthcare
Belle, A., Thiagarajan, R., Soroushmehr, S. M. R., Navidi, F., Beard, D. A., & Najarian, K. (2015) · BioMed Research International · doi:10.1155/2015/370194 · Cited by 527 · see citing works
Metabolic modeling of single Th17 cells reveals regulators of autoimmunity
Wagner, A., Wang, C., Fessler, J., DeTomaso, D., Avila-Pacheco, J., Kaminski, J., Zaghouani, S., Christian, E., Thakore, P., Schellhaass, B., et al. (2021) · Cell · doi:10.1016/j.cell.2021.05.045 · Cited by 524 · see citing works
Mardinoğlu, A., Ågren, R., Kampf, C., Asplund, A., Uhlén, M., & Nielsen, J. (2014) · Nature Communications · doi:10.1038/ncomms4083 · Cited by 520 · see citing works
Self-citationMTAP deletions in cancer create vulnerability to targeting of the MAT2A/PRMT5/RIOK1 axis
Marjon, K., Cameron, M. J., Quang, P., Clasquin, M. F., Mandley, E., Kunii, K., McVay, M., Choe, S., Kernytsky, A., Gross, S., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.03.043 · Cited by 485 · see citing works
Metabolite Measurement: Pitfalls to Avoid and Practices to Follow
Lu, W., Su, X., Klein, M. S., Lewis, I. A., Fiehn, O., & Rabinowitz, J. D. (2017) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-061516-044952 · Cited by 457 · see citing works
Robinson, J. L., Kocabaş, P., Wang, H., Cholley, P.-E., Cook, D., Nilsson, A., Anton, M., Ferreira, R., Domenzain, I., Billa, V., et al. (2020) · Science Signaling · doi:10.1126/scisignal.aaz1482 · Cited by 442 · see citing works
Self-citationQuantitative and logic modelling of molecular and gene networks
Novère, N. G. L. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3885 · Cited by 422 · see citing works
Challenges and emergent solutions for LC‐MS/MS based untargeted metabolomics in diseases
Liang, C., Lu, H., & Lee, Y. H. (2018) · Mass Spectrometry Reviews · doi:10.1002/mas.21562 · Cited by 419 · see citing works
Noronha, A., Modamio, J., Jarosz, Y., Guerard, E., Sompairac, N., Preciat, G., Daníelsdóttir, A. D., Krecké, M., Merten, D., Haraldsdóttir, H. S., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky992 · Cited by 383 · see citing works
Self-citationCurrin, A., Swainston, N., Day, P. J., & Kell, D. B. (2014) · Chemical Society Reviews · doi:10.1039/c4cs00351a · Cited by 383 · see citing works
Self-citationÅgren, R., Mardinoğlu, A., Asplund, A., Kampf, C., Uhlén, M., & Nielsen, J. (2014) · Molecular Systems Biology · doi:10.1002/msb.145122 · Cited by 372 · see citing works
Self-citationMulti-omics integration in biomedical research – A metabolomics-centric review
Wörheide, M. A., Krumsiek, J., Kastenmüller, G., & Arnold, M. (2020) · Analytica Chimica Acta · doi:10.1016/j.aca.2020.10.038 · Cited by 359 · see citing works
Pathway Commons 2019 Update: integration, analysis and exploration of pathway data
Rodchenkov, I. V., Babur, Ö., Luna, A., Aksoy, B. A., Wong, J. V., Fong, D., Franz, M., Siper, M. C., Cheung, M., Wrana, M., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz946 · Cited by 306 · see citing works
Defining the Metabolome: Size, Flux, and Regulation
Zamboni, N., Saghatelian, A., & Patti, G. J. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.04.021 · Cited by 299 · see citing works
The biology of ergothioneine, an antioxidant nutraceutical
Borodina, I., Kenny, L. C., McCarthy, C. M., Paramasivan, K., Pretorius, E., Roberts, T. J., van der Hoek, S. A., & Kell, D. B. (2020) · Nutrition Research Reviews · doi:10.1017/s0954422419000301 · Cited by 296 · see citing works
“1), and no endogenous genome-encoded metabolites from Recon2(56) contain the”
BackgroundSelf-citationReconstructing organisms in silico: genome-scale models and their emerging applications
Fang, X., Lloyd, C. J., & Palsson, B. O. (2020) · Nature Reviews Microbiology · doi:10.1038/s41579-020-00440-4 · Cited by 292 · see citing works
Self-citationDifferential Glutamate Metabolism in Proliferating and Quiescent Mammary Epithelial Cells
Coloff, J. L., Murphy, J. P., Braun, C. R., Harris, I. S., Shelton, L. M., Kami, K., Gygi, S. P., Selfors, L. M., & Brugge, J. S. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2016.03.016 · Cited by 288 · see citing works
Recon 2.2: from reconstruction to model of human metabolism
Swainston, N., Smallbone, K., Hefzi, H., Dobson, P. D., Brewer, J., Hanscho, M., Zielinski, D. C., Ang, K. S., Gardiner, N. J., Gutierrez, J. M., et al. (2016) · Metabolomics · doi:10.1007/s11306-016-1051-4 · Cited by 285 · see citing works
Self-citationBasu, S., Duren, W. L., Evans, C. R., Burant, C., Michailidis, G. C., & Karnovsky, A. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx012 · Cited by 267 · see citing works
Proteome-wide analysis of cysteine oxidation reveals metabolic sensitivity to redox stress
van der Reest, J., Lilla, S., Zheng, L., Zanivan, S. R., & Gottlieb, E. (2018) · Nature Communications · doi:10.1038/s41467-018-04003-3 · Cited by 267 · see citing works
A guide to 13C metabolic flux analysis for the cancer biologist
Antoniewicz, M. R. (2018) · Experimental & Molecular Medicine · doi:10.1038/s12276-018-0060-y · Cited by 264 · see citing works
Emerging roles for lipids in non-apoptotic cell death
Magtanong, L., Ko, P., & Dixon, S. J. (2016) · Cell Death and Differentiation · doi:10.1038/cdd.2016.25 · Cited by 259 · see citing works
Evaluation and comparison of bioinformatic tools for the enrichment analysis of metabolomics data
Marco‐Ramell, A., Palau‐Rodriguez, M., Alay, A., Tulipani, S., Urpí-Sardà, M., Sánchez‐Pla, Á., & Andrés‐Lacueva, C. (2018) · BMC Bioinformatics · doi:10.1186/s12859-017-2006-0 · Cited by 261 · see citing works
A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism
Hefzi, H., Ang, K. S., Hanscho, M., Bordbar, A., Ruckerbauer, D. E., Lakshmanan, M., Orellana, C. A., Baycin‐Hizal, D., Huang, Y., Ley, D., et al. (2016) · Cell Systems · doi:10.1016/j.cels.2016.10.020 · Cited by 253 · see citing works
Self-citationFast Reconstruction of Compact Context-Specific Metabolic Network Models
Vlassis, N. A., Pacheco, M. P., & Sauter, T. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003424 · Cited by 257 · see citing works
Metabolite exchange between mammalian organs quantified in pigs
Jang, C., Hui, S., Zeng, X., Cowan, A. J., Wang, L., Chen, L., Morscher, R. J., Reyes, J., Frezza, C., Hwang, H. Y., et al. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2019.06.002 · Cited by 256 · see citing works
Molecular phenotyping of a UK population: defining the human serum metabolome
Dunn, W. B., Lin, W., Broadhurst, D., Begley, P., Brown, M., Zelena, E., Vaughan, A. A., Halsall, A., Harding, N., Knowles, J. D., et al. (2014) · Metabolomics · doi:10.1007/s11306-014-0707-1 · Cited by 251 · see citing works
Self-citationSung, J., Kim, S., Cabatbat, J. J. T., Jang, S., Jin, Y., Jung, G. Y., Chia, N., & Kim, P. (2017) · Nature Communications · doi:10.1038/ncomms15393 · Cited by 249 · see citing works
Nielsen, J. (2017) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-061516-044757 · Cited by 252 · see citing works
Self-citationProceedings of the 2017 Winter Simulation Conference
Chan, W.-M., D’Ambrogio, A., Zacharewicz, G., Mustafee, N., Wainer, G., & Page, E. (2017) · HAL · Cited by 251 · see citing works
Computational Metabolomics: A Framework for the Million Metabolome
Uppal, K., Walker, D. I., Liu, K., Li, S., Go, Y., & Jones, D. P. (2016) · Chemical Research in Toxicology · doi:10.1021/acs.chemrestox.6b00179 · Cited by 241 · see citing works
Global implementation of genomic medicine: We are not alone
Manolio, T. A., Abramowicz, M. J., Al‐Mulla, F., Anderson, W. P., Balling, R., Berger, A. C., Bleyl, S. B., Chakravarti, A., Chantratita, W., Chisholm, R. L., et al. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aab0194 · Cited by 239 · see citing works
A systematic assessment of current genome-scale metabolic reconstruction tools
Mendoza, S. N., Olivier, B. G., Molenaar, D., & Teusink, B. (2019) · Genome biology · doi:10.1186/s13059-019-1769-1 · Cited by 230 · see citing works
Big data in IBD: big progress for clinical practice
Seyed Tabib, N. S., Madgwick, M., Sudhakar, P., Verstockt, B., Korcsmaros, T., & Vermeire, S. (2020) · Gut · doi:10.1136/gutjnl-2019-320065 · Cited by 223 · see citing works
Menstrual cycle rhythmicity: metabolic patterns in healthy women
Draper, C. F., Duisters, K., Weger, B., Chakrabarti, A., Harms, A. C., Brennan, L., Hankemeier, T., Goulet, L., Konz, T., Martin, F. P., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-32647-0 · Cited by 221 · see citing works
A Systematic Evaluation of Methods for Tailoring Genome-Scale Metabolic Models
Opdam, S., Richelle, A., Kellman, B. P., Li, S., Zielinski, D. C., & Lewis, N. E. (2017) · Cell Systems · doi:10.1016/j.cels.2017.01.010 · Cited by 209 · see citing works
Cutshaw, G., Uthaman, S., Hassan, N. M., Kothadiya, S., Wen, X., & Bardhan, R. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.2c00897 · Cited by 204 · see citing works
Lamichhane, S., Sen, P., Dickens, A. M., Orešič, M., & Bertram, H. C. (2018) · Methods · doi:10.1016/j.ymeth.2018.04.029 · Cited by 200 · see citing works
Optimizing genome-scale network reconstructions
Monk, J. M., Nogales, J., & Palsson, B. Ø. (2014) · Nature Biotechnology · doi:10.1038/nbt.2870 · Cited by 200 · see citing works
Self-citationSystems Biology of Metabolism: A Driver for Developing Personalized and Precision Medicine
Nielsen, J. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.02.002 · Cited by 197 · see citing works
Self-citationMembrane transporter engineering in industrial biotechnology and whole cell biocatalysis
Kell, D. B., Swainston, N., Pir, P., & Oliver, S. G. (2015) · Trends in biotechnology · doi:10.1016/j.tibtech.2015.02.001 · Cited by 195 · see citing works
Self-citationCoene, K. L. M., Kluijtmans, L. A. J., van der Heeft, E., Engelke, U. F. H., de Boer, S., Hoegen, B., Kwast, H. J. T., van de Vorst, M., Huigen, M. C. D. G., Keularts, I. M. L. W., et al. (2018) · Journal of Inherited Metabolic Disease · doi:10.1007/s10545-017-0131-6 · Cited by 195 · see citing works
Modeling cancer metabolism on a genome scale
Yizhak, K., Chaneton, B., Gottlieb, E., & Ruppin, E. (2015) · Molecular Systems Biology · doi:10.15252/msb.20145307 · Cited by 182 · see citing works
Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions
Blais, E. M., Rawls, K. D., Dougherty, B. V., Li, Z. I., Kolling, G. L., Ye, P., Wallqvist, A., & Papin, J. A. (2017) · Nature Communications · doi:10.1038/ncomms14250 · Cited by 182 · see citing works
Self-citationDevelopment and Quantitative Evaluation of a High-Resolution Metabolomics Technology
Liu, X., Ser, Z., & Locasale, J. W. (2014) · Analytical Chemistry · doi:10.1021/ac403845u · Cited by 174 · see citing works
Revealing disease-associated pathways by network integration of untargeted metabolomics
Pirhaji, L., Milani, P., Leidl, M., Curran, T., Avila-Pacheco, J., Clish, C. B., White, F. M., Saghatelian, A., & Fraenkel, E. (2016) · Nature Methods · doi:10.1038/nmeth.3940 · Cited by 167 · see citing works
COMBINE archive and OMEX format: one file to share all information to reproduce a modeling project
Bergmann, F. T., Adams, R., Moodie, S., Cooper, J., Glont, M., Golebiewski, M., Hucka, M., Laibe, C., Miller, A. K., Nickerson, D. P., et al. (2014) · BMC Bioinformatics · doi:10.1186/s12859-014-0369-z · Cited by 173 · see citing works
Self-citationPath2Models: large-scale generation of computational models from biochemical pathway maps
Büchel, F., Rodríguez, N., Swainston, N., Wrzodek, C., Czauderna, T., Keller, R., Mittag, F., Schubert, M., Glont, M., Golebiewski, M., et al. (2013) · BMC Systems Biology · doi:10.1186/1752-0509-7-116 · Cited by 173 · see citing works
Self-citationKell, D. B., & Goodacre, R. (2013) · Drug Discovery Today · doi:10.1016/j.drudis.2013.07.014 · Cited by 169 · see citing works
Self-citationMetabolic shifts in residual breast cancer drive tumor recurrence
Havas, K. M., Milchevskaya, V., Radic, K., Alladin, A., Kafkia, E., Garcia, M., Stolte, J., Klaus, B., Rotmensz, N., Gibson, T. J., et al. (2017) · Journal of Clinical Investigation · doi:10.1172/jci89914 · Cited by 168 · see citing works
Metabolomics and Diabetes: Analytical and Computational Approaches
Sas, K. M., Karnovsky, A., Michailidis, G. C., & Pennathur, S. (2015) · Diabetes · doi:10.2337/db14-0509 · Cited by 169 · see citing works
Crowdsourcing biomedical research: leveraging communities as innovation engines
Sáez-Rodríguez, J., Costello, J. C., Friend, S. H., Kellen, M., Mangravite, L. M., Meyer, P., Norman, T., & Stolovitzky, G. A. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.69 · Cited by 165 · see citing works
ElRakaiby, M. T., Dutilh, B. E., Rizkallah, M. R., Boleij, A., Cole, J. N., & Aziz, R. K. (2014) · OMICS A Journal of Integrative Biology · doi:10.1089/omi.2014.0018 · Cited by 167 · see citing works
Hertel, J., Harms, A. C., Heinken, A., Baldini, F., Thinnes, C. C., Glaab, E., Vasco, D. A., Pietzner, M., Stewart, I. D., Wareham, N. J., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.10.035 · Cited by 162 · see citing works
Self-citationKell, D. B., & Oliver, S. G. (2014) · Frontiers in Pharmacology · doi:10.3389/fphar.2014.00231 · Cited by 155 · see citing works
Self-citationGraph Curvature for Differentiating Cancer Networks
Sandhu, R., Georgiou, T. T., Reznik, E., Zhu, L., Kolesov, I., Şenbabaoğlu, Y., & Tannenbaum, A. (2015) · Scientific Reports · doi:10.1038/srep12323 · Cited by 168 · see citing works
Applications of Genome-Scale Metabolic Models in Biotechnology and Systems Medicine
Zhang, C., & Hua, Q. (2016) · Frontiers in Physiology · doi:10.3389/fphys.2015.00413 · Cited by 150 · see citing works
Transcriptomics resources of human tissues and organs
Uhlén, M., Hallström, B. M., Lindskog, C., Mardinoğlu, A., Pontén, F., & Nielsen, J. (2016) · Molecular Systems Biology · doi:10.15252/msb.20155865 · Cited by 144 · see citing works
Self-citationA model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes
Smallbone, K., Messiha, H. L., Carroll, K. M., Winder, C. L., Malys, N., Dunn, W. B., Murabito, E., Swainston, N., Dada, J. O., Khan, F., et al. (2013) · FEBS Letters · doi:10.1016/j.febslet.2013.06.043 · Cited by 147 · see citing works
Self-citationRedox control of glutamine utilization in cancer
Alberghina, L., & Gaglio, D. (2014) · Cell Death and Disease · doi:10.1038/cddis.2014.513 · Cited by 147 · see citing works
Huang, S., Chong, N. Y. Y., Lewis, N. E., Jia, W. P., Xie, G., & Garmire, L. X. (2016) · Genome Medicine · doi:10.1186/s13073-016-0289-9 · Cited by 144 · see citing works
Ortmayr, K., Dubuis, S., & Zampieri, M. (2019) · Nature Communications · doi:10.1038/s41467-019-09695-9 · Cited by 142 · see citing works
Reconstruction of Tissue-Specific Metabolic Networks Using CORDA
Schultz, A., & Qutub, A. A. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004808 · Cited by 133 · see citing works
Phenotype-based cell-specific metabolic modeling reveals metabolic liabilities of cancer
Yizhak, K., Gaude, E., Dévédec, S. E. L., Waldman, Y. Y., Stein, G. Y., van de Water, B., Frezza, C., & Ruppin, E. (2014) · eLife · doi:10.7554/elife.03641 · Cited by 135 · see citing works
The self-inhibitory nature of metabolic networks and its alleviation through compartmentalization
Alam, M. T., Olín‐Sandoval, V., Stincone, A., Keller, M. A., Zelezniak, A., Luisi, B. F., & Ralser, M. (2017) · Nature Communications · doi:10.1038/ncomms16018 · Cited by 136 · see citing works
Ravcheev, D. A., & Thiele, I. (2017) · Frontiers in Genetics · doi:10.3389/fgene.2017.00111 · Cited by 136 · see citing works
Self-citationBiological insights through nontargeted metabolomics
Sévin, D. C., Kuehne, A., Zamboni, N., & Sauer, U. (2014) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2014.10.001 · Cited by 134 · see citing works
Deep learning meets metabolomics: a methodological perspective
Sen, P., Lamichhane, S., Mathema, V. B., McGlinchey, A. J., Dickens, A. M., Khoomrung, S., & Orešič, M. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa204 · Cited by 133 · see citing works
Mitochondrial metabolism supports resistance to IDH mutant inhibitors in acute myeloid leukemia
Stuani, L., Sabatier, M., Wang, F., Poupin, N., Bosc, C., Saland, E., Castelli, F. A., Gales, L., Montersino, C., Boët, E., et al. (2021) · The Journal of Experimental Medicine · doi:10.1084/jem.20200924 · Cited by 131 · see citing works
Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks
Fröhlich, F., Kaltenbacher, B., Theis, F. J., & Hasenauer, J. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005331 · Cited by 132 · see citing works
Designing and interpreting ‘multi-omic’ experiments that may change our understanding of biology
Haas, R., Zelezniak, A., Iacovacci, J., Kamrad, S., Townsend, S., & Ralser, M. (2017) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.08.009 · Cited by 131 · see citing works
Chylek, L. A., Harris, L. A., Tung, C., Faeder, J. R., Lopez, C. F., & Hlavacek, W. S. (2013) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.1245 · Cited by 131 · see citing works
Tebani, A., Abily-Donval, L., Afonso, C., Marret, S., & Bekri, S. (2016) · International Journal of Molecular Sciences · doi:10.3390/ijms17071167 · Cited by 129 · see citing works
Irizar, P. A., Schäuble, S., Esser, D., Groth, M., Frahm, C., Priebe, S., Baumgart, M., Hartmann, N., Marthandan, S., Menzel, U., et al. (2018) · Nature Communications · doi:10.1038/s41467-017-02395-2 · Cited by 122 · see citing works
The metabolome 18 years on: a concept comes of age
Kell, D. B., & Oliver, S. G. (2016) · Metabolomics · doi:10.1007/s11306-016-1108-4 · Cited by 127 · see citing works
Self-citationModeling metabolism of the human gut microbiome
Magnúsdóttir, S., & Thiele, I. (2018) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2017.12.005 · Cited by 127 · see citing works
Self-citationExtending the small-molecule similarity principle to all levels of biology with the Chemical Checker
Duran-Frigola, M., Pauls, E., Guitart-Pla, O., Bertoni, M., Alcalde, V., Amat, D., Juan-Blanco, T., & Aloy, P. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0502-7 · Cited by 126 · see citing works
Mitochondrial Regulation of the Hippocampal Firing Rate Set Point and Seizure Susceptibility
Styr, B., Gonen, N., Zarhin, D., Ruggiero, A., Atsmon, R., Gazit, N., Braun, G., Frère, S. G. A., Vertkin, I., Shapira, I., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.03.045 · Cited by 126 · see citing works
Perspectives on Systems Modeling of Human Peripheral Blood Mononuclear Cells
Sen, P., Kemppainen, E., & Orešič, M. (2018) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2017.00096 · Cited by 124 · see citing works
fast G ap F ill : efficient gap filling in metabolic networks
Thiele, I., Vlassis, N. A., & Fleming, R. M. T. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu321 · Cited by 123 · see citing works
Self-citationGenome-Scale Model Reveals Metabolic Basis of Biomass Partitioning in a Model Diatom
Levering, J., Broddrick, J. T., Dupont, C. L., Peers, G., Beeri, K., Mayers, J. J., Gallina, A. A., Allen, A. E., Palsson, B. Ø., & Zengler, K. (2016) · PLoS ONE · doi:10.1371/journal.pone.0155038 · Cited by 122 · see citing works
Self-citationGenome scale metabolic modeling of cancer
Nilsson, A., & Nielsen, J. (2016) · Metabolic Engineering · doi:10.1016/j.ymben.2016.10.022 · Cited by 118 · see citing works
Self-citation
- Authors
- Thiele, I., Swainston, N., Fleming, R. M. T., Hoppe, A., Sahoo, S., Aurich, M. K., Haraldsdottir, H., Mo, M. L., Rolfsson, O., Stobbe, M. D., Thorleifsson, S. G., Agren, R., Bölling, C., Bordel, S., Chavali, A. K., Dobson, P., Dunn, W. B., Endler, L., Hala, D., Hucka, M., Hull, D., Jameson, D., Jamshidi, N., Jonsson, J. J., Juty, N., Keating, S., Nookaew, I., Le Novère, N., Malys, N., Mazein, A., Papin, J. A., Price, N. D., Selkov, E., Sigurdsson, M. I., Simeonidis, E., Sonnenschein, N., Smallbone, K., Sorokin, A., van Beek, J. H. G. M., Weichart, D., Goryanin, I., Nielsen, J., Westerhoff, H. V., Kell, D. B., Mendes, P., & Palsson, B. Ø.
- Affiliations
- University of Iceland (IS)
- University of Manchester (GB)
- Charité – Universitätsmedizin Berlin (DE)
- University of California San Diego (US)
- Netherlands Bioinformatics Centre (NL)
- Chalmers University of Technology (SE)
- University of Virginia (US)
- University of Sheffield (GB)
- Manchester Academic Health Science Centre (GB)
- University of Vienna (AT)
- University of North Texas (US)
- California Institute of Technology (US)
- European Bioinformatics Institute (GB)
- University of Edinburgh (GB)
- Institute for Systems Biology (US)
- University of Luxembourg (LU)
- Constructor University (DE)
- Russian Academy of Sciences (RU)
- Okinawa Institute of Science and Technology Graduate University (JP)
- Corresponding author
- Thiele, Ines
- ORCID
- Thiele, Ines
- Swainston, Neil
- Fleming, Ronan M T
- Hoppe, Andreas
- Sahoo, Swagatika
- Stobbe, Miranda D
- Bordel, Sergio
- Dobson, Paul
- Dunn, Warwick B
- Endler, Lukas
- Hala, David
- Hucka, Michael
- Hull, Duncan
- Jameson, Daniel
- Jamshidi, Neema
- Juty, Nick
- Keating, Sarah
- Nookaew, Intawat
- Malys, Naglis
- Mazein, Alexander
- Papin, Jason A
- Price, Nathan D
- Sigurdsson, Martin I
- Sonnenschein, Nikolaus
- Sorokin, Anatoly
- Goryanin, Igor
- Nielsen, Jens
- Westerhoff, Hans V
- Kell, Douglas B
- Mendes, Pedro
- Palsson, Bernhard Ø
- Venue
- Nature Biotechnology
- Published
- 2013-03-03
- Volume
- 31
- Issue
- 5
- Pages
- 419-425
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC3856361
- OpenAlex
- W2132218677
- Cited by
- 1,019
- References
- 52
- Citations by year
- 2026: 28 · 2025: 35 · 2024: 45 · 2023: 45 · 2022: 45 · 2021: 60 · 2020: 82 · 2019: 93 · 2018: 101 · 2017: 125 · 2016: 98 · 2015: 116 · 2014: 95 · 2013: 51
- FWCI
- 53.59
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- MIMS EPrints (University of Southampton) (acceptedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Chalmers Publication Library (Chalmers University of Technology) (acceptedVersion)
- Open Repository and Bibliography (University of Luxembourg) (submittedVersion, other-oa)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion)
- Research Explorer (The University of Manchester) (submittedVersion, other-oa)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- Chalmers Research (Chalmers University of Technology) (submittedVersion)
- Hirsla (Landspítali University Hospital) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- National Science Foundation (0643548, 0315756)
- Bioprocessing Research Industry Club
- European Commission (249261, 201142)
- Knut och Alice Wallenbergs Stiftelse
- National Institutes of Health
- Directorate for Biological Sciences
- Engineering and Physical Sciences Research Council (BBC0082191)
- Biotechnology and Biological Sciences Research Council (BB/C008219/1, BB/E006248/1, BBS/E/B/000C0419, BB/C008219, BB/J019305/1, BB/F00561X, 201142, BB/F005938)
- Science and Technology Facilities Council
- National Cancer Institute
- National Institute of General Medical Sciences (R01GM080219, R01GM070923, R01GM088244, GM088244, U01GM102098)
- FP7 Ideas: European Research Council (232816)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- metabolic network topology, inborn errors of metabolism, metabolic biomarkers, metabolomics data integration, protein expression data
- MeSH terms
- Computer Simulation, Humans, Models, Biological, Proteome, Databases, Protein, Metabolome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review