Suchergebnisse

Mbebi, A. J., Tong, H. & Nikoloski, Z. L2,1-norm regularized multivariate regression model with applications to genomic prediction. Bioinformatics (2021). doi:10.1093/bioinformatics/btab212

Tong, H., Küken, A., Razaghi-Moghadam, Z. & Nikoloski, Z. Characterization of effects of genetic variants via genome-scale metabolic modelling. Cellular and Molecular Life Sciences 78, 5123–5138 (2021).

Tong, H. & Nikoloski, Z. Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data. Journal of Plant Physiology 257, (2021).

Tong, H., Küken, A. & Nikoloski, Z. Integrating molecular markers into metabolic models improves genomic selection for Arabidopsis growth. Nature Communications 11, (2020).

Cubillos, A., Tong, H., Alseekh, S., de Abreu e Lima, F., Yu, J., Fernie, A. R., Nikoloski, Z. & Laitinen, R. Inheritance patterns in metabolism and growth in diallel crosses of Arabidopsis thaliana from a single growth habitat. Heredity 120, 463–473 (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, (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., Willmitzer, L. & Brotman, Y. Mapping the Arabidopsis Metabolic Landscape by Untargeted Metabolomics at Different Environmental Conditions. Molecular Plant 11, 118–134 (2018).