Yeast9: a consensus genome-scale metabolic model for S. cerevisiae curated by the community

Autor: Chengyu Zhang, Benjamín J Sánchez, Feiran Li, Cheng Wei Quan Eiden, William T Scott, Ulf W Liebal, Lars M Blank, Hendrik G Mengers, Mihail Anton, Albert Tafur Rangel, Sebastián N Mendoza, Lixin Zhang, Jens Nielsen, Hongzhong Lu, Eduard J Kerkhoven

Publikováno v: Molecular Systems Biology, Vol 20, Iss 10, Pp 1134-1150 (2024)

Abstract Genome-scale metabolic models (GEMs) can facilitate metabolism-focused multi-omics integrative analysis. Since Yeast8, the yeast-GEM of Saccharomyces cerevisiae, published in 2019, has been continuously updated by the community. This has inc

Externí odkaz: https://doaj.org/article/6ceac2e6fd9f4f218e5ca5c7ed65211e

Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0

Autor: Iván Domenzain, Benjamín Sánchez, Mihail Anton, Eduard J. Kerkhoven, Aarón Millán-Oropeza, Céline Henry, Verena Siewers, John P. Morrissey, Nikolaus Sonnenschein, Jens Nielsen

Publikováno v: Nature Communications, Vol 13, Iss 1, Pp 1-13 (2022)

Abstract Genome-scale metabolic models (GEMs) have been widely used for quantitative exploration of the relation between genotype and phenotype. Streamlined integration of enzyme constraints and proteomics data into such models was first enabled by t

Externí odkaz: https://doaj.org/article/2c658bb1c7854350acfe1f06f530ec04

GotEnzymes: an extensive database of enzyme parameter predictions

Autor: Jens Nielsen, Mihail Anton, Feiran Li, Yu Chen

Publikováno v: Nucleic Acids Research. 51:D583-D586

Enzyme parameters are essential for quantitatively understanding, modelling, and engineering cells. However, experimental measurements cover only a small fraction of known enzyme-compound pairs in model organisms, much less in other organisms. Artifi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06bcdd05ec7c3038a1340eacbaa585ff
https://doi.org/10.1093/nar/gkac831

Generation and analysis of context-specific genome-scale metabolic models derived from single-cell RNA-Seq data

Autor: Johan Gustafsson, Mihail Anton, Fariba Roshanzamir, Rebecka Jörnsten, Eduard J. Kerkhoven, Jonathan L. Robinson, Jens Nielsen

Publikováno v: Proceedings of the National Academy of Sciences. 120

Single-cell RNA sequencing combined with genome-scale metabolic models (GEMs) has the potential to unravel the differences in metabolism across both cell types and cell states but requires new computational methods. Here, we present a method for gene

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0947ba1f56f4cbb938f4f1d3bbda495b
https://doi.org/10.1073/pnas.2217868120

Genome-scale metabolic network reconstruction of model animals as a platform for translational research

Autor: Mattias Uhlen, Shan Huang, Thomas Svensson, Pınar Kocabaş, Jonathan L. Robinson, Mihail Anton, Hao Wang, Johan Gustafsson, Johan Gobom, Pierre-Etienne Cholley, Jens Nielsen, Henrik Zetterberg

Publikováno v: Wang, H, Robinson, J L, Kocabas, P, Gustafsson, J, Anton, M, Cholley, P-E, Huang, S, Gobom, J, Svensson, T, Uhlen, M, Zetterberg, H & Nielsen, J 2021, ' Genome-scale metabolic network reconstruction of model animals as a platform for translational research ', Proceedings of the National Academy of Sciences of the United States of America, vol. 118, no. 30, e2102344118 . https://doi.org/10.1073/pnas.2102344118
Proceedings of the National Academy of Sciences of the United States of America

Significance Animal models and genome-scale metabolic models (GEMs) are two important tools for studying human diseases, but a proper integration of the two is lacking. To bridge them, we developed a reproducible and systematic framework by which the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92af6dff02b13d4bad687b44724a9b6a
https://orbit.dtu.dk/en/publications/534c2a92-5e5e-41e7-9d52-ba7c208fe4ae