Publikationen von Z. Nikoloski

Zeitschriftenartikel (207)

61.
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Nowak, J.; Eng, R.C.; Matz, T.; Waack, M.; Persson, S.; Sampathkumar, A.; Nikoloski, Z.: A network-based framework for shape analysis enables accurate characterization of leaf epidermal cells. Nature Communications 12 (1), 458 (2021)
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Beleggia, R.; Omranian, N.; Holtz, Y.; Gioia, T.; Fiorani, F.; Nigro, F.M.; Pecchioni, N.; De Vita, P.; Schurr, U.; David, J.L. et al.; Nikoloski, Z.; Papa, R.: Comparative analysis based on transcriptomics and metabolomics data reveal differences between emmer and durum wheat in response to nitrogen starvation. International Journal of Molecular Sciences 22 (9), 4790 (2021)
63.
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Küken, A.; Wendering, P.; Langary, D.; Nikoloski, Z.: A structural property for reduction of biochemical networks. Scientific Reports 11 (1), 17415 (2021)
64.
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Mbebi, A. J.; Tong, H.; Nikoloski, Z.: L2,1-norm regularized multivariate regression model with applications to genomic prediction. Bioinformatics 37 (18), S. 2896 - 2904 (2021)
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Omranian, N.; Angeleska, A.; Nikoloski, Z.: PC2P: parameter-free network-based prediction of protein complexes. Bioinformatics 37 (1), S. 73 - 81 (2021)
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Pries, C.; Razaghi-Moghadam, Z.; Kopka, J.; Nikoloski, Z.: Integration of relative metabolomics and transcriptomics time-course data in a metabolic model pinpoints effects of ribosome biogenesis defects on Arabidopsis thaliana metabolism. Scientific Reports 11 (1), 4787 (2021)
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Razaghi-Moghadam, Z.; Sokolowska, E.; Sowa, M.A.; Skirycz, A.; Nikoloski, Z.: Combination of network and molecule structure accurately predicts competitive inhibitory interactions. Computational and Structural Biotechnology Journal 19, S. 2170 - 2178 (2021)
68.
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Seep, L.; Razaghi-Moghadam, Z.; Nikoloski, Z.: Reaction lumping in metabolic networks for application with thermodynamic metabolic flux analysis. Scientific Reports 11, 8544 (2021)
69.
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Tong, H.; Nikoloski, Z.: Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data. Journal of Plant Physiology 257, 153354 (2021)
70.
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Nowak, J.; Gennermann, K.; Persson, S.; Nikoloski, Z.: CytoSeg 2.0: automated extraction of actin filaments. Bioinformatics 36 (9), S. 2950 - 2951 (2020)
71.
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Clemente-Moreno, M.; Omranian, N.; Sáez, P.; Figueroa, C.; Del-Saz, N.; Elso, M.; Poblete, L.; Orf, I.; Cuadros-Inostroza, A.; Cavieres, L.A. et al.; Bravo, L.; Fernie, A. R.; Ribas-Carbó, M.; Flexas, J.; Nikoloski, Z.; Brotman, Y.; Gago, J.: Low temperature tolerance of the Antarctic species Deschampsia antarctica: a complex metabolic response associated with nutrient remobilization. Plant, Cell and Environment 43 (6), S. 1376 - 1393 (2020)
72.
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Correa, S. M.; Alseekh, S.; Atehortúa, L.; Brotman, Y.; Ríos-Estepa, R.; Fernie, A. R.; Nikoloski, Z.: Model-assisted identification of metabolic engineering strategies for Jatropha curcas lipid pathways. The Plant Journal (angenommen)
73.
Zeitschriftenartikel
Correa, S. M.; Fernie, A. R.; Nikoloski, Z.; Brotman, Y.: Towards model-driven characterization and manipulation of plant lipid metabolism. Progress in Lipid Research 80, 101051 (2020)
74.
Zeitschriftenartikel
Küken, A.; Gennermann, K.; Nikoloski, Z.: Characterization of maximal enzyme catalytic rates in central metabolism of Arabidopsis thaliana. The Plant Journal 103 (6), S. 2168 - 2177 (2020)
75.
Zeitschriftenartikel
Lyall, R.; Nikoloski, Z.; Gechev, T.: Comparative analysis of ros network genes in extremophile eukaryotes. International Journal of Molecular Sciences 21 (23), S. 1 - 27 (2020)
76.
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Razaghi-Moghadam, Z.; Nikoloski, Z.: Supervised Learning of Gene Regulatory Networks. Current Protocols in Plant Biology 5 (2), e20106 (2020)
77.
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Robaina-Estévez, S.; Nikoloski, Z.: Flux-based hierarchical organization of Escherichia coli’s metabolic network. PLoS Computational Biology 16 (4), e1007832 (2020)
78.
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Tong, H.; Küken, A.; Nikoloski, Z.: Integrating molecular markers into metabolic models improves genomic selection for Arabidopsis growth. Nature Communications 11 (1), 2410 (2020)
79.
Zeitschriftenartikel
Angeleska, A.; Nikoloski, Z.: Coherent network partitions. Discrete applied mathematics 266, S. 283 - 290 (2019)
80.
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Clemente-Moreno, J. M.; Omranian, N.; Sáez, P.; Figueroa, C. M.; Del-Saz, N.; Elso, M.; Poblete, L.; Orf, I.; Cuadros-Inostroza, A.; Cavieres, L. et al.; Bravo, L.; Fernie, A. R.; Ribas-Carbó, M.; Flexas, J.; Nikoloski, Z.; Brotman, Y.; Gago, J.: Cytochrome respiration pathway and sulphur metabolism sustain stress tolerance to low temperature in the Antarctic species Colobanthus quitensis. New Phytologist 225 (2), S. 754 - 768 (2019)
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