Suchergebnisse

Cuadros-Inostroza, Á.; Verdugo-Alegría, C.; Willmitzer, L.; Moreno-Simunovic, Y.; Vallarino, J. G.: Non-Targeted Metabolite Profiles and Sensory Properties Elucidate Commonalities and Differences of Wines Made with the Same Variety but Different Cultivar Clones. Metabolites 10 (6), E220 (2020)

Pott, D. M.; Vallarino, J. G.; Cruz-Rus, E.; Willmitzer, L.; Sanchez-Sevilla, J. F.; Amaya, I.; Osorio, S.: Genetic analysis of phenylpropanoids and antioxidant capacity in strawberry fruit reveals mQTL hotspots and candidate genes. Scientific Reports 10 (1), 20197 (2020)

Pott, D. M.; de Abreu e Lima, F.; Soria, C.; Willmitzer, L.; Fernie, A. R.; Nikoloski, Z.; Osorio, S.; Vallarino, J. G.: Metabolic reconfiguration of strawberry physiology in response to postharvest practices. Food Chemistry 321, 126747 (2020)

Vallarino, J.G.; Merchante, C.; Sánchez-Sevilla, J.F.; de Luis Balaguer, M.A.; Pott, D.M.; Ariza, M.T.; Casañal, A.; Posé, D.; Vioque, A.; Amaya, I. et al.; Willmitzer, L.; Solano, R.; Sozzani, R.; Fernie, A. R.; Botella, M.A.; Giovannoni, J.J.; Valpuesta, V.; Osorio, S.: Characterizing the involvement of FaMADS9 in the regulation of strawberry fruit receptacle development. Plant Biotechnology Journal 18 (4), S. 929 - 943 (2020)

Al-Aama, J.; Al Mahdi, H. B.; Salama, M. A.; Bakur, K.; Alhozali, A.; Mosli, H.; Bahijri, S. M.; Bahieldin, A.; Elango, R.; Willmitzer, L. et al.; Edris, S.: Rapid detection of type II diabetes mellitus in Saudi patients via simultaneous screening of multiple SNPs. Biotechnology & Biotechnology Equipment 33 (1), S. 1319 - 1326 (2019)

Al-Aama, J.Y.; Mahdi, H.B.A.; Salama, M.A.; Bakur, K.H.; Alhozali, A.; Mosli, H.H.; Bahijri, S.M.; Bahieldin, A.; Willmitzer, L.; Edris, S.: Detection of secondary metabolites as biomarkers for the early diagnosis and prevention of type 2 diabetes. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy 12, S. 2675 - 2684 (2019)

Bozek, K.; Khrameeva, E. E.; Reznick, J.; Omerbašić, D.; Bennett, N. C.; Lewin, G. R.; Azpurua, J.; Gorbunova, V.; Seluanov, A.; Regnard, P. et al.; Wanert, F.; Marchal, J.; Pifferi, F.; Aujard, F.; Liu, Z.; Shi, P.; Pääbo, S.; Schröder, F.; Willmitzer, L.; Giavalisco, P.; Khaitovich, P.: Publisher Correction: Lipidome determinants of maximal lifespan in mammals. Scientific Reports 9 (1), 6972 (2019)

Goehring, I.; Sauter, N. S.; Catchpole, G.; Assmann, A.; Shu, L.; Zien, K. S.; Moehlig, M.; Pfeiffer, A. F. H.; Oberholzer, J.; Willmitzer, L. et al.; Spranger, J.; Maedler, K.: Correction to: Identification of an intracellular metabolic signature impairing beta cell function in the rat beta cell line INS-1E and human islets. Diabetologia 62 (3), S. 553 - 554 (2019)

Goehring, I.; Sauter, N. S.; Catchpole, G.; Assmann, A.; Shu, L.; Zien, K. S.; Moehlig, M.; Pfeiffer, A. F. H.; Oberholzer, J.; Willmitzer, L. et al.; Spranger, J.; Maedler, K.: Identification of an intracellular metabolic signature impairing beta cell function in the rat beta cell line INS-1E and human islets (vol 54, pg 2584, 2011). Diabetologia 62 (3), S. 553 - 554 (2019)

Kurochkin, I.; Khrameeva, E.; Tkachev, A.; Stepanova, V.; Vanyushkina, A.; Stekolshchikova, E.; Li, Q.; Zubkov, D.; Shichkova, P.; Halene, T. et al.; Willmitzer, L.; Giavalisco, P.; Akbarian, S.; Khaitovich, P.: Metabolome signature of autism in the human prefrontal cortex. Communications Biology 2 (1), 234 (2019)

Zhang, Q.; Wu, S.; Li, Y.; Liu, M.; Ni, K.; Yi, X.; Shi, Y.; Ma, L.; Willmitzer, L.; Ruan, J.: Characterization of three different classes of non-fermented teas using untargeted metabolomics. Food Research International 121, S. 697 - 704 (2019)

de Abreu e Lima, F.; Li, K.; Wen, W.; Yan, J.; Nikoloski, Z.; Willmitzer, L.; Brotman, Y.: Unraveling lipid metabolism in maize with time-resolved multi-omics data. The Plant Journal 93 (6), S. 1102 - 1115 (2018)

de Abreu e Lima, F.; Willmitzer, L.; Nikoloski, Z.: Classification-driven framework to predict maize hybrid field performance from metabolic profiles of young parental roots. PLoS One 13 (4), e0196038 (2018)

Vallarino, J. G.; de Abreu e Lima, F.; Soria, C.; Tong, H.; Pott, D. M.; Willmitzer, L.; Fernie, A. R.; Nikoloski, Z.; Osorio, S.: Genetic diversity of strawberry germplasm using metabolomic biomarkers. Scientific Reports 8 (1), 14386 (2018)

Veyel, D.; Sokolowska, E.; Moreno, J.C.; Kierszniowska, S.; Cichon, J.; Wojciechowska, I.; Luzarowski, M.; Kosmacz, M.; Szlachetko, J.; Gorka, M. et al.; Meret, M.; Graf, A.; Meyer, E. H.; Willmitzer, L.; Skirycz, A.: PROMIS, global analysis of PROtein-metabolite interactions using size separation in Arabidopsis thaliana. The Journal of Biological Chemistry 293 (32), S. 12440 - 12453 (2018)

Wen, W.; Jin, M.; Li, K.; Liu, H.; Xiao, Y.; Zhao, M.; Alseekh, S.; Li, W.; de Abreu e Lima, F.; Brotman, Y. et al.; Willmitzer, L.; Fernie, A. R.; Yan, J.: An integrated multi-layered analysis of the metabolic networks of different tissues uncovers key genetic components of primary metabolism in maize. The Plant Journal 93 (6), S. 1116 - 1128 (2018)

Wu, S.; Tohge, T.; Cuadros-Inostroza, A. C.; Tong, H.; Tenenboim, H.; Kooke, R.; Méret, M.; Keurentjes, J. B.; Nikoloski, Z.; Fernie, A. R. et al.; Willmitzer, L.; Brotman, Y.: Mapping the Arabidopsis Metabolic Landscape by Untargeted Metabolomics at Different Environmental Conditions. Molecular Plant 11 (1), S. 118 - 134 (2018)

Bozek, K.; Khrameeva, E. E.; Reznick, J.; Omerbašić, D.; Bennett, N. C.; Lewin, G. R.; Azpurua, J.; Gorbunova, V.; Seluanov, A.; Regnard, P. et al.; Wanert, F.; Marchal, J.; Pifferi, F.; Aujard, F.; Liu, Z.; Shi, P.; Pääbo, S.; Schröder, F.; Willmitzer, L.; Giavalisco, P.; Khaitovich, P.: Lipidome determinants of maximal lifespan in mammals. Scientific Reports 7, 5 (2017)

Bucher, R.; Veyel, D.; Willmitzer, L.; Krattinger, S.; Keller, B.; Biglera, L.: Combined GC- and UHPLC-HR-MS Based Metabolomics to Analyze Durable Anti-fungal Resistance Processes in Cereals. Chimia 71 (4), S. 156 - 159 (2017)

de Abreu e Lima, F.; Westhues, M.; Cuadros-Inostroza, Á.; Willmitzer, L.; Melchinger, A. E.; Nikoloski, Z.: Metabolic robustness in young roots underpins a predictive model of maize hybrid performance in the field. The Plant Journal 90 (2), S. 319 - 329 (2017)