Saklayen, M. G. The global epidemic of the metabolic syndrome. Curr. Hypertens. Rep. 20, 12 (2018).
Article PubMed PubMed Central Google Scholar
Martínez-Reyes, I. & Chandel, N. S. Cancer metabolism: looking forward. Nat. Rev. Cancer 21, 669–680 (2021).
Xu, Y. et al. An atlas of genetic scores to predict multi-omic traits. Nature 616, 123–131 (2023).
Article CAS PubMed PubMed Central Google Scholar
Aaltonen, L. A. et al. Pan-cancer analysis of whole genomes. Nature 578, 82–93 (2020).
Mardinoglu, A. & Nielsen, J. Systems medicine and metabolic modelling. J. Intern. Med. 271, 142–154 (2012). An extensive review of the use of GEMs in systems medicine-based applications.
Article CAS PubMed Google Scholar
Hyduke, D. R., Lewis, N. E. & Palsson, B. Ø. Analysis of omics data with genome-scale models of metabolism. Mol. Biosyst. 9, 167–174 (2013).
Article CAS PubMed Google Scholar
Hasin, Y., Seldin, M. & Lusis, A. Multi-omics approaches to disease. Genome Biol. 18, 83 (2017).
Article PubMed PubMed Central Google Scholar
Palsson, B. & Zengler, K. The challenges of integrating multi-omic data sets. Nat. Chem. Biol. 6, 787–789 (2010).
Mardinoglu, A., Boren, J., Smith, U., Uhlen, M. & Nielsen, J. Systems biology in hepatology: approaches and applications. Nat. Rev. Gastroenterol. Hepatol. 15, 365–377 (2018). An extensive review of the studies that use biological networks for integration of multiomics data for complex liver diseases.
Article CAS PubMed Google Scholar
Bajwa, J., Munir, U., Nori, A. & Williams, B. Artificial intelligence in healthcare: transforming the practice of medicine. Future Healthc. J. 8, e188–e194 (2021).
Article PubMed PubMed Central Google Scholar
Oberhardt, M. A., Palsson, B. Ø. & Papin, J. A. Applications of genome-scale metabolic reconstructions. Mol. Syst. Biol. 5, 320 (2009).
Article PubMed PubMed Central Google Scholar
Mardinoglu, A., Gatto, F. & Nielsen, J. Genome-scale modeling of human metabolism — a systems biology approach. Biotechnol. J. 8, 985–996 (2013). An extensive review of the algorithms for the reconstruction of cell- and tissue- type specific GEMs.
Article CAS PubMed Google Scholar
O’Brien, E. J., Monk, J. M. & Palsson, B. O. Using genome-scale models to predict biological capabilities. Cell 161, 971–987 (2015).
Article PubMed PubMed Central Google Scholar
Nielsen, J. Systems biology of metabolism: a driver for developing personalized and precision medicine. Cell Metab. 25, 572–579 (2017).
Article CAS PubMed Google Scholar
Wagner, A. et al. Metabolic modeling of single Th17 cells reveals regulators of autoimmunity. Cell 184, 4168–4185.e21 (2021).
Article CAS PubMed PubMed Central Google Scholar
Yizhak, K., Chaneton, B., Gottlieb, E. & Ruppin, E. Modeling cancer metabolism on a genome scale. Mol. Syst. Biol. 11, 817 (2015).
Article PubMed PubMed Central Google Scholar
Terekhanova, N. V. et al. Epigenetic regulation during cancer transitions across 11 tumour types. Nature 623, 432–441 (2023).
Article CAS PubMed PubMed Central Google Scholar
Duarte, N. C. et al. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc. Natl Acad. Sci. USA 104, 1777–1782 (2007). This study presents the first global human GEM and its use for systems biology-based applications.
Article CAS PubMed PubMed Central Google Scholar
Ma, H. et al. The Edinburgh Human Metabolic Network reconstruction and its functional analysis. Mol. Syst. Biol. 3, 135 (2007).
Article PubMed PubMed Central Google Scholar
Hao, T., Ma, H. W., Zhao, X. M. & Goryanin, I. Compartmentalization of the Edinburgh Human Metabolic Network. BMC Bioinformatics 11, 393 (2010).
Article PubMed PubMed Central Google Scholar
Palsson, B. Ø. Systems Biology: Constraint-Based Reconstruction and Analysis (Cambridge Univ. Press, 2015).
Agren, R. et al. Reconstruction of genome-scale active metabolic networks for 69 human cell types and 16 cancer types using INIT. PLoS Comput. Biol. 8, e1002518 (2012).
Article CAS PubMed PubMed Central Google Scholar
Thiele, I. et al. A community-driven global reconstruction of human metabolism. Nat. Biotechnol. 31, 419–425 (2013).
Article CAS PubMed Google Scholar
Mardinoglu, A. et al. Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease. Nat. Commun. 5, 3083 (2014).
Gille, C. et al. HepatoNet1: a comprehensive metabolic reconstruction of the human hepatocyte for the analysis of liver physiology. Mol. Syst. Biol. 6, 411 (2010).
Article PubMed PubMed Central Google Scholar
Mardinoglu, A. et al. Integration of clinical data with a genome-scale metabolic model of the human adipocyte. Mol. Syst. Biol. 9, 649 (2013).
Article CAS PubMed PubMed Central Google Scholar
Kanehisa, M. in ‘In Silico’ Simulation of Biological Processes: Novartis Foundation Symposium 247 (eds. Bock, G. & Goode, J. A.) 91–103 (Wiley, 2002).
Milacic, M. et al. The Reactome Pathway Knowledgebase 2024 Nucleic Acids Res. 52, D672–D678 (2024).
Quek, L.-E. et al. Reducing Recon 2 for steady-state flux analysis of HEK cell culture. J. Biotechnol. 184, 172–178 (2014).
Article CAS PubMed Google Scholar
Smallbone, K. Striking a balance with Recon 2.1. Preprint at arXiv https://doi.org/10.48550/arXiv.1311.5696 (2014).
Swainston, N. et al. Recon 2.2: from reconstruction to model of human metabolism. Metabolomics 12, 109 (2016).
Article PubMed PubMed Central Google Scholar
Brunk, E. et al. Recon3D enables a three-dimensional view of gene variation in human metabolism. Nat. Biotechnol. 36, 272–281 (2018). This paper presents the community-based global reconstruction of human metabolism.
Article CAS PubMed PubMed Central Google Scholar
Robinson, J. L. et al. An atlas of human metabolism. Sci. Signal. 13, eaaz1482 (2020). This paper presents an extensively curated global human GEM that unifies two parallel model lineages.
Article CAS PubMed PubMed Central Google Scholar
Dahal, S., Yurkovich, J. T., Xu, H., Palsson, B. O. & Yang, L. Synthesizing systems biology knowledge from omics using genome-scale models. Proteomics 20, 1900282 (2020).
Mardinoglu, A. & Nielsen, J. New paradigms for metabolic modeling of human cells. Curr. Opin. Biotechnol. 34, 91–97 (2015).
留言 (0)