Publications 2022

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

Hashemi S, Razaghi-Moghadam Z, Laitinen R , Nikoloski Z.
Relative flux trade-offs and optimization of metabolic network functionalities.
Computational and Structural Biotechnology Journal, Volume 20, 2022, Pages 3963-3971

Huß, S, Judd, R S, Koper, K, Maeda, H A, Nikoloski, Z.
An automated workflow that generates atom mappings for large-scale metabolic models and its application to Arabidopsis thaliana.
Plant J, 111: 1486-1500

Hashemi S, Laitinen R, Nikoloski Z.
Models and molecular mechanisms for trade-offs in the context of metabolism.
Authorea Preprints; 2022

Matz T W, Wang Y, Kulshreshtha R, Sampathkumar A, Nikoloski Z.
Topological properties accurately predict cell division events and organization of shoot apical meristem in Arabidopsis thaliana.
Development 15 August 2022; 149 (16): dev201024

Ferreira M A d M, Silveira W B d, Nikoloski Z.
PARROT: Prediction of enzyme abundances using protein-constrained metabolic models.
Authorea Preprints; 2022.

Mbebi AJ, Breitler JC, Bordeaux M, Sulpice R, McHale M, Tong H, Toniutti L, Castillo JA, Bertrand B, Nikoloski Z.
A comparative analysis of genomic and phenomic predictions of growth-related traits in 3-way coffee hybrids.
G3: Genes| Genomes| Genetics. 2022 Sep;12(9).