Veröffentlichungen 2021

    Universität Potsdam - Institut für Biochemie und Biologie - AG Bioinformatik - Veröffentlichungen – 2021

    Aarabi F, Rakpenthai A, Barahimipour R, Gorka M, Alseekh S, Zhang, Y, Salem M. A, Brückner F, Omranian N, Watanabe, M, Nikoloski Z, Giavalisco P, Tohge T, Graf A, Fernie A. R, Hoefgen R.
    Sulfur Deficiency Induced genes affect seed protein accumulation and composition under sulfate deprivation.
    Plant Physiol, 2021 Aug; kiab386

    Angeleska A, Omranian N, Nikoloski Z.
    Coherent network partitions: Characterizations with cographs and prime graphs.
    Theoretical computer science, 2021 Oct.

    Beleggia R, Omranian N, Holtz Y, Gioia T,Razaghi-Moghadam, Z, Nikoloski, Z.
    GeneReg: a constraint-based approach for design of feasible metabolic engineering strategies at the gene level.
    Bioinformatics, 2021 Jun; 37(12):1717-1723

    Duarte G. T, Pandey P. K, Vaid N, Alseekh S, Fernie A. R, Nikoloski Z, Laitinen R. A. E.
    Plasticity of rosette size in response to nitrogen availability is controlled by an R C C 1-family protein.
    Plant Cell Environ, 2021 Oct; 44(10):3398--3411

    Eng R. C, Schneider R, Matz T. W, Carter R, Ehrhardt D. W, Jönsson H, Nikoloski Z, Sampathkumar A.
    KATANIN and CLASP function at different spatial scales to mediate microtubule response to mechanical stress in Arabidopsis cotyledons.
    Curr Biol, 2021 Aug; 31 (15):3262–3274

    Fiorani F, Nigro FM, Pecchioni N, De Vita P, Schurr U, David JL, Nikoloski Z, Papa R .
    Comparative Analysis Based on Transcriptomics and Metabolomics Data Reveal Differences between Emmer and Durum Wheat in Response to Nitrogen Starvation.
    Int J Mol Sci, 2021 Apr; 22(9)

    Hashemi S, Zahra Razaghi-Moghadam Z, Nikoloski Z.
    Identification of flux trade-offs in metabolic networks
    Scientific Reports. 2021 Dec; 11:23776

    Küken A, Wendering P, Langary D,  Nikoloski, Z.
    A structural property for reduction of biochemical networks.
    Sci Rep, 2021 Aug; 11(1):17415

    Mbebi AJ, Tong H, Nikoloski Z.
    L2,1-norm regularized multivariate regression model with applications to genomic prediction.
    Bioinformatics, 2021 Sep: 37(18):2896-2904

    Moreno J. C, Rojas B. E, Vicente R, Gorka M, Matz T, Chodasiewicz M, Peralta-Ariza J. S,  Zhang, Y, Alseekh S, Childs D, Luzarowski M, Nikoloski Z, Zarivach R, Walther D, Hartman M. D, Figueroa C. M, Iglesias A. A, Fernie A. R, Skirycz, A.
    Tyr-Asp inhibition of glyceraldehyde 3-phosphate dehydrogenase affects plant redox metabolism.
    MBO J, 2021 Aug; 40(15):e106800

    Nowak J, Eng RC, Matz T, Waack M, Persson S, Sampathkumar A, Nikoloski Z.
    A network-based framework for shape analysis enables accurate characterization of leaf epidermal cells.
    Nat Commun, 2021 Jan; 12(1):458

    Omranian N, Angeleska A, Nikoloski Z.
    Efficient and accurate identification of protein complexes from protein-protein interaction networks based on the clustering coefficient.
    Computational and Structural Biotechnology Journal 19, pp. 5255 - 5263 (2021)

    Omranian S, Angeleska A, Nikoloski, Z.
    PC2P: Parameter-free network-based prediction of protein complexes.
    Bioinformatics, 2021 Jan; 37(1):73-81

    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.
    Sci Rep, 2021 Feb; 11(1):4787

    Razaghi-Moghadam Z, Sokolowska E. M, Sowa M. A, Skirycz A, Nikoloski Z.
    Combination of network and molecule structure accurately predicts competitive inhibitory interactions.
    Comput Struct Biotechnol J, 2021; 19:2170-2178

    Seep L, Razaghi-Moghadam Z, Nikoloski Z.
    Reaction lumping in metabolic networks for application with thermodynamic metabolic flux analysis.
    Sci Rep, 2021 Apr; 11(1):8544

    Tong H, Küken A, Razaghi-Moghadam Z, Nikoloski Z.
    Characterization of effects of genetic variants via genome-scale metabolic modelling.
    Cell Mol Life Sci, 2021 Jun;78(12):5123-5138

    Tong H, Nikoloski, Z.
    Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data.
    J Plant Physiol, 2021 Feb; 257:153354

    Xu R, Razaghi-Moghadam Z, Nikoloski, Z.
    Maximization of non-idle enzymes improves the coverage of the estimated maximal in vivo enzyme catalytic rates in Escherichia coli.
    Bioinformatics, 2021 Aug.

    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, 2021 Oct; koab251

    Zimmer D, Swart C, Graf A, Arrivault S, Tillich M, Proost S, Nikoloski Z, Stitt M, Bock R, Mühlhaus T, Boulouis A.
    Topology of the redox network during induction of photosynthesis as revealed by time-resolved proteomics in tobacco.
    Science advances 7 (51), 2021 Dec; eabi8307