Publikationen der Gruppe

Wendering, P.; Andreou, G.M.; Laitinen, R.A.E.; Nikoloski, Z.: Metabolic modeling identifies determinants of thermal growth responses in Arabidopsis thaliana. New Phytologist 247 (1), S. 178 - 190 (2025)

Langary, D.; Küken, A.; Nikoloski, Z.: Kinetic modules are sources of concentration robustness in biochemical networks. Science Advances 11 (22), eads7269 (2025)

Mbebi, A. J.; Mercado, F.; Hobby, D.; Tong, H.; Nikoloski, Z.: Advances in multi-trait genomic prediction approaches: classification, comparative analysis, and perspectives. Briefings in Bioinformatics 26 (3), bbaf211 (2025)

Hobby, D.; Tong, H.; Heuermann, M.; Mbebi, A. J.; Laitinen, R. A. E.; Dell’Acqua, M.; Altmann, T.; Nikoloski, Z.: Predicting plant trait dynamics from genetic markers. Nature Plants 11, S. 1018 - 1027 (2025)

Hsieh, Y. E.; Yang, S.-Y.; Liu, S.-L.; Wang, S.-W.; Wang, W.-L.; Tang, S.-L.; Yang, S.-H.: Microbial Community Shifts and Nitrogen Utilization in Peritidal Microbialites: The Role of Salinity and pH in Microbially Induced Carbonate Precipitation. Microbial Ecology 88 (1), 31 (2025)

Seyis, M.; Razaghi-Moghadam, Z.; Nikoloski, Z.: Flux-sum coupling analysis of metabolic network models. PLOS Computational Biology 21 (4), e1012972 (2025)

de Moura Ferreira, M. A.; Menezes de Almeida, E. L.; Batista da Silveira, W.; Nikoloski, Z.: Protein-constrained models pinpoints the role of underground metabolism in robustness of metabolic phenotypes. iScience 28 (3), 112126 (2025)

Yuan, Y.; Iannetta, A.; Kim, M.; Sadecki, P.; Arend, M.; Tsichla, A.; Ruiz-Sola, M.; Kepesidis, G.; Falconet, D.; Thevenon, E. et al.; Tardif, M.; Brugière, S.; Couté, Y.; Kleman, J.; Sizova, I.; Schilling, M.; Jouhet, J.; Hegemann, P.; Li-Beisson, Y.; Nikoloski, Z.; Bastien, O.; Hicks, L.; Petroutsos, D.: Phototropin connects blue light perception to starch metabolism in green algae. Nature Communications 16, 2545 (2025)

Correa Cordoba, S. M.; Burgos, A.; Cuadros-Inostroza, A. C.; Xu, K.; Brotman, Y.; Nikoloski, Z.: A data-integrative modeling approach accurately characterizes the effects of mutations on Arabidopsis lipid metabolism. Plant Physiology 197 (2), kiae615 (2025)

Hsieh, Y. E.; Tandon, K.; Verbruggen, H.; Nikoloski, Z.: Integration of metatranscriptomics data improves the predictive capacity of microbial community metabolic models. The ISME Journal 19 (1), wraf109 (2025)

Razaghi-Moghadam, Z.; Soleymani Babadi, F.; Nikoloski, Z.: Harnessing the optimization of enzyme catalytic rates in engineering of metabolic phenotypes. PLOS Computational Biology 20 (11), e1012576 (2024)

Habibpour , M.; Razaghi-Moghadam, Z.; Nikoloski, Z.: Machine learning of metabolite-protein interactions from model-derived metabolic phenotypes. NAR: genomics and bioinformatics 6 (3), lqae114 (2024)

Qian, L.; Yan, B.; Zhou, J.; Fan, Y.; Tao, M.; Zhu, W.; Wang, C.; Tu, Q.; Tian, Y.; He, Q. et al.; Wu, K.; Niu, M.; Yan, Q.; Nikoloski, Z.; Liu, G.; Yu, X.; He, Z.: Comprehensive profiles of sulfur cycling microbial communities along a mangrove sediment depth. Science of the Total Environment 944, 173961 (2024)

Rahimi-Majd, M.; Leverett, A.; Neumann, A.; Kromdijk, J.; Nikoloski, Z.: Nonlinear models based on leaf architecture traits explain the variability of mesophyll conductance across plant species. Plant, Cell and Environment 47 (12), S. 5158 - 5171 (2024)

Pieri, A.; Beleggia, R.; Gioia, T.; Tong, H.; Di Vittori, V.; Frascarelli, G.; Bitocchi, E.; Nanni, L.; Bellucci, E.; Fiorani, F. et al.; Pecchioni, N.; Marzario, S.; De Quattro, C.; Limongi, A.; De Vita, P.; Rossato, M.; Schurr, U.; David, J.; Nikoloski, Z.; Papa, R.: Transcriptomic response to nitrogen availability reveals signatures of adaptive plasticity during tetraploid wheat domestication. Plant Cell 36 (9), S. 3809 - 3823 (2024)

Hsieh, Y. E.; Tandon, K.; Verbruggen, H.; Nikoloski, Z.: Comparative analysis of metabolic models of microbial communities reconstructed from automated tools and consensus approaches. npj Systems biology and applications 10 (1), 54 (2024)

Laitinen, R. A. E.; Nikoloski, Z.: Strategies to identify and dissect trade-offs in plants. Molecular Ecology 33 (10), e16780 (2024)

Gupta, S.; Petrov, V.; Garg, V.; Mueller-Roeber, B.; Fernie, A. R.; Nikoloski, Z.; Gechev, T.: The genome of Haberlea rhodopensis provides insights into the mechanisms for tolerance to multiple extreme environments. Cellular and Molecular Life Sciences 81 (1), 117 (2024)

Habibpour, M.; Razaghi-Moghadam, Z.; Nikoloski, Z.: Prediction and integration of metabolite-protein interactions with genome-scale metabolic models. Metabolic Engineering 82, S. 216 - 224 (2024)

Hsieh, Y.; Lu, C.-Y.; Liu, P.-Y.; Kao, J.-M.; Yang, S.-Y.; Wu, C.-Y.; Wong, J.-W.M.; Shikina, S.; Fan, T.-Y.; Yang, S.-H.: Successive responses of three coral holobiont components (coral hosts, symbiotic algae, and bacteria) to daily temperature fluctuations. Ecological Indicators 158, 111515 (2024)