University of Potsdam - Institute of Biochemistry and Biology- Bioinformatics group - Publications - 2022
Zhu F, Alseekh S, Koper K, Tong H, Nikoloski Z, Naake T, Liu H, Yan J, Brotman Y, Wen W, Maeda H, Cheng Y, Fernie A R.
Genome-wide association of the metabolic shifts underpinning dark-induced senescence in Arabidopsis
The Plant Cell, 2022 Jan; 34 (1), 557–578
Wendering P, Nikoloski Z, Hug L A, Shi J.
Genome-Scale Modeling Specifies the Metabolic Capabilities of Rhizophagus irregularis
mSystems, 2022 Jan; 7 (1) 01216-21
Treves H, Küken A, Arrivault S, Ishihara H, Hoppe I, Erban A, Höhne M, Moraes T. A, Kopka J, Szymanski J, Nikoloski Z, Stitt M.
Carbon flux through photosynthesis and central carbon metabolism show distinct patterns between algae, C3 and C4 plants.
Nature plants 8 (1), 78-91
Wendering P, Arend M, Nikoloski Z.
Estimates of in vivo turnover numbers by simultaneously considering data from multiple conditions improve metabolic predictions.
bioRxiv, 2022 Jan
Tong H, Nankar AN, Liu J, Todorova V, Ganeva D, Grozeva S, Tringovska I, Pasev G, Radeva-Ivanova V, Gechev T, Kostova D, Nikoloski Z.
Genomic prediction of morphometric and colorimetric traits in Solanaceous fruits.
Horticulture Research, Volume 9, 2022, uhac072
Arend M, Yuan Y, Águila Ruiz-Sola M, Omranian N, Nikoloski Z, Petroutsos D.
Widening the landscape of transcriptional regulation of algal photoprotection
bioRxiv 2022.02.25.482034
Wendering P, Nikoloski Z.
COMMIT: Consideration of metabolite leakage and community composition improves microbial community reconstructions.
PLoS computational biology 18 (3), e1009906
Küken A, Langary D, Nikoloski Z.
The hidden simplicity of metabolic networks is revealed by multireaction dependencies.
Science advances 8 (13), eabl6962
Liu Z, Østerlund I, Ruhnow F, Cao Y, Huang G, Cai W, Zhang J, Liang W, Nikoloski Z, Persson S, Zhang D.
Fluorescent cytoskeletal markers reveal associations between the actin and microtubule cytoskeleton in rice cells.
Development (2022) 149 (12): dev200415
Omranian S, Nikoloski Z, Grimm D. G.
Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward.
Computational and Structural Biotechnology Journal, 2022 May
Arend M, Yuan Y, Águila Ruiz-Sola M, Omranian N, Nikoloski Z, Petroutsos D.
Data integration across conditions improves turnover number estimates and metabolic predictions.
bioRxiv 2022.04.01.486742