World's Best Scientists 2026 revealed!

D-Index & Metrics

Biology and Biochemistry

D-Index
58
Citations
13113
World Ranking
13098
National Ranking
932

Zoran Nikoloski publication distribution in Biology and Biochemistry in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Biology and Biochemistry in 2026. The highlighted bar marks where Zoran Nikoloski sits on this spectrum.

47–56 publications: 8 scientists 57–66 publications: 35 scientists 67–76 publications: 106 scientists 77–86 publications: 231 scientists 87–96 publications: 414 scientists 97–106 publications: 546 scientists 107–116 publications: 704 scientists 117–126 publications: 849 scientists 127–136 publications: 980 scientists 137–146 publications: 942 scientists 147–156 publications: 969 scientists 157–166 publications: 950 scientists 167–176 publications: 951 scientists 177–186 publications: 915 scientists 187–196 publications: 787 scientists 197–206 publications: 841 scientists 207–216 publications: 735 scientists 217–226 publications: 709 scientists 227–236 publications: 651 scientists 237–246 publications: 605 scientists 247–256 publications: 510 scientists 257–266 publications: 524 scientists 267–276 publications: 434 scientists 277–286 publications: 418 scientists 287–296 publications: 350 scientists 297–306 publications: 363 scientists 307–316 publications: 315 scientists 317–326 publications: 296 scientists 327–336 publications: 261 scientists 337–346 publications: 240 scientists 347–356 publications: 219 scientists 357–366 publications: 197 scientists 367–376 publications: 154 scientists 377–386 publications: 161 scientists 387–396 publications: 155 scientists 397–406 publications: 145 scientists 407–416 publications: 124 scientists 417–426 publications: 112 scientists 427–436 publications: 132 scientists 437–446 publications: 116 scientists 447–456 publications: 99 scientists 457–466 publications: 81 scientists 467–476 publications: 91 scientists 477–486 publications: 80 scientists 487–496 publications: 80 scientists 497–506 publications: 60 scientists 507–516 publications: 36 scientists 517–526 publications: 46 scientists 527–536 publications: 54 scientists 537–546 publications: 44 scientists 547–556 publications: 43 scientists 557–566 publications: 43 scientists 567–576 publications: 42 scientists 577–586 publications: 25 scientists 587–596 publications: 34 scientists 597–606 publications: 23 scientists 607–616 publications: 33 scientists 617–626 publications: 31 scientists 627–636 publications: 27 scientists 637–646 publications: 25 scientists 647–656 publications: 28 scientists 657–666 publications: 34 scientists 667–676 publications: 18 scientists 677–686 publications: 16 scientists 687–696 publications: 10 scientists 697–706 publications: 12 scientists 707–716 publications: 21 scientists 717–726 publications: 12 scientists 727–736 publications: 12 scientists 737–746 publications: 10 scientists 747–756 publications: 7 scientists 757–766 publications: 13 scientists 767–776 publications: 15 scientists 777–786 publications: 13 scientists 787–796 publications: 9 scientists 797–806 publications: 9 scientists 807–816 publications: 7 scientists 817–826 publications: 4 scientists 827–836 publications: 9 scientists 837–846 publications: 7 scientists 847–856 publications: 3 scientists 857–866 publications: 5 scientists 867–876 publications: 5 scientists 877–886 publications: 11 scientists 887–896 publications: 3 scientists 897–906 publications: 4 scientists 907–916 publications: 7 scientists 917–926 publications: 5 scientists 927–936 publications: 6 scientists 937–946 publications: 6 scientists 947–956 publications: 3 scientists 957–966 publications: 7 scientists 967–976 publications: 2 scientists 977–986 publications: 2 scientists 987–996 publications: 1 scientists 997–1,006 publications: 5 scientists 1,007–1,016 publications: 2 scientists 1,017–1,026 publications: 2 scientists 1,027 publications: 1 scientists 1,028+ publications: 100 scientists
47 publications 1,028+

This scientist: 280 publications — 74th percentile

74% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,028 publications or more.

Zoran Nikoloski D-index placement in Biology and Biochemistry in 2026

The chart shows the D-index (discipline H-index) distribution of Biology and Biochemistry scientists ranked by Research.com in 2026. The highlighted bar marks where Zoran Nikoloski sits on this spectrum.

40–41 D-Index: 80 scientists 42–43 D-Index: 183 scientists 44–45 D-Index: 317 scientists 46–47 D-Index: 504 scientists 48–49 D-Index: 718 scientists 50–51 D-Index: 900 scientists 52–53 D-Index: 1,026 scientists 54–55 D-Index: 1,150 scientists 56–57 D-Index: 1,236 scientists 58–59 D-Index: 1,253 scientists 60–61 D-Index: 1,163 scientists 62–63 D-Index: 1,131 scientists 64–65 D-Index: 1,032 scientists 66–67 D-Index: 897 scientists 68–69 D-Index: 814 scientists 70–71 D-Index: 715 scientists 72–73 D-Index: 709 scientists 74–75 D-Index: 596 scientists 76–77 D-Index: 512 scientists 78–79 D-Index: 473 scientists 80–81 D-Index: 412 scientists 82–83 D-Index: 373 scientists 84–85 D-Index: 358 scientists 86–87 D-Index: 285 scientists 88–89 D-Index: 273 scientists 90–91 D-Index: 227 scientists 92–93 D-Index: 208 scientists 94–95 D-Index: 193 scientists 96–97 D-Index: 153 scientists 98–99 D-Index: 157 scientists 100–101 D-Index: 148 scientists 102–103 D-Index: 120 scientists 104–105 D-Index: 113 scientists 106–107 D-Index: 100 scientists 108–109 D-Index: 86 scientists 110–111 D-Index: 67 scientists 112–113 D-Index: 72 scientists 114–115 D-Index: 73 scientists 116–117 D-Index: 64 scientists 118–119 D-Index: 53 scientists 120–121 D-Index: 60 scientists 122–123 D-Index: 54 scientists 124–125 D-Index: 43 scientists 126–127 D-Index: 38 scientists 128–129 D-Index: 49 scientists 130–131 D-Index: 26 scientists 132–133 D-Index: 18 scientists 134–135 D-Index: 23 scientists 136–137 D-Index: 32 scientists 138–139 D-Index: 32 scientists 140–141 D-Index: 27 scientists 142–143 D-Index: 19 scientists 144–145 D-Index: 22 scientists 146–147 D-Index: 12 scientists 148–149 D-Index: 16 scientists 150–151 D-Index: 14 scientists 152–153 D-Index: 10 scientists 154–155 D-Index: 13 scientists 156–157 D-Index: 10 scientists 158–159 D-Index: 7 scientists 160–161 D-Index: 9 scientists 162–163 D-Index: 13 scientists 164–165 D-Index: 4 scientists 166 D-Index: 4 scientists 167+ D-Index: 98 scientists
40 D-Index 167+

This scientist: 58 D-Index — 34th percentile

34% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 167 D-Index or more.

Overview

Zoran Nikoloski is affiliated with the Max Planck Institute of Molecular Plant Physiology in Germany. Their research spans multiple domains within biochemistry, genetics, and molecular biology, with significant contributions focused on molecular biology and plant science. The primary fields of study include:

  • Biochemistry, Genetics and Molecular Biology
  • Agricultural and Biological Sciences

Their subfields of expertise incorporate molecular biology, plant science, genetics, biomedical engineering, and renewable energy, sustainability, and the environment. Key subfields are:

  • Molecular Biology
  • Plant Science
  • Genetics
  • Biomedical Engineering
  • Renewable Energy, Sustainability and the Environment

Nikoloski's research topics cover several focused areas including microbial metabolic engineering and bioproduction, bioinformatics and genomic networks, biofuel production and bioconversion, gene regulatory network analysis, photosynthetic processes and mechanisms, genetic mapping and diversity in plants and animals, and algal biology and biofuel production. The main topics of their work are:

  • Microbial Metabolic Engineering and Bioproduction
  • Bioinformatics and Genomic Networks
  • Biofuel production and bioconversion
  • Gene Regulatory Network Analysis
  • Photosynthetic Processes and Mechanisms
  • Genetic Mapping and Diversity in Plants and Animals
  • Algal biology and biofuel production

Frequent collaborators in their research include Philipp Wendering, Zahra Razaghi-Moghadam, Hao Tong, Anika Küken, and Marius Arend.

Nikoloski has published extensively in various scientific venues, with the most frequent being:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Nature Communications
  • PLoS Computational Biology
  • Scientific Reports

Notable recent papers authored or co-authored by Nikoloski include:

  • Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data, 2020, Journal of Plant Physiology
  • Carbon flux through photosynthesis and central carbon metabolism show distinct patterns between algae, C3 and C4 plants, 2021, Nature Plants
  • KATANIN and CLASP function at different spatial scales to mediate microtubule response to mechanical stress in Arabidopsis cotyledons, 2021, Current Biology
  • A Biostimulant Obtained from the Seaweed Ascophyllum nodosum Protects Arabidopsis thaliana from Severe Oxidative Stress, 2020, International Journal of Molecular Sciences
  • Genome-wide association of the metabolic shifts underpinning dark-induced senescence in Arabidopsis, 2021, The Plant Cell

Best Publications

  • On Modularity Clustering

    U. Brandes;D. Delling;M. Gaertler;R. Gorke

  • Metabolic control and regulation of the tricarboxylic acid cycle in photosynthetic and heterotrophic plant tissues.

    Wagner L. Araújo;Adriano Nunes-Nesi;Zoran Nikoloski;Lee J. Sweetlove

  • Metabolic Fluxes in an Illuminated Arabidopsis Rosette

    Marek Szecowka;Robert Heise;Takayuki Tohge;Adriano Nunes-Nesi

  • PlaNet: Combined Sequence and Expression Comparisons across Plant Networks Derived from Seven Species

    Marek Mutwil;Sebastian Klie;Takayuki Tohge;Federico M Giorgi

  • On finding graph clusterings with maximum modularity

    Ulrik Brandes;Daniel Delling;Marco Gaertler;Robert Görke

  • Genome Wide Association in tomato reveals 44 candidate loci for fruit metabolic traits

    Christopher Sauvage;Vincent Segura;Guillaume Bauchet;Rebecca Stevens

  • Maximizing Modularity is hard

    U. Brandes;D. Delling;M. Gaertler;R. Goerke

  • Identification and Mode of Inheritance of Quantitative Trait Loci for Secondary Metabolite Abundance in Tomato

    Saleh Alseekh;Takayuki Tohge;Regina Wendenberg;Federico Scossa

  • Integrative Comparative Analyses of Transcript and Metabolite Profiles from Pepper and Tomato Ripening and Development Stages Uncovers Species-Specific Patterns of Network Regulatory Behavior

    Sonia Osorio;Rob Alba;Zoran Nikoloski;Andrej Kochevenko

  • Metabolic variation between japonica and indica rice cultivars as revealed by non-targeted metabolomics

    Chaoyang Hu;Jianxin Shi;Sheng Quan;Bo Cui

  • Relationships of Leaf Net Photosynthesis, Stomatal Conductance, and Mesophyll Conductance to Primary Metabolism: A Multispecies Meta-Analysis Approach

    Jorge Gago;Danilo de Menezes Daloso;Carlos María Figueroa;Jaume Flexas

  • Genetic Determinants of the Network of Primary Metabolism and Their Relationships to Plant Performance in a Maize Recombinant Inbred Line Population

    Weiwei Wen;Weiwei Wen;Kun Li;Saleh Alseekh;Nooshin Omranian

  • Metabolite profiling and network analysis reveal coordinated changes in grapevine water stress response

    Uri Hochberg;Asfaw Degu;David Toubiana;Tanya Gendler

  • Gene regulatory network inference using fused LASSO on multiple data sets.

    Nooshin Omranian;Jeanne M. O. Eloundou-Mbebi;Bernd Mueller-Roeber;Zoran Nikoloski

  • Systems Analysis of the Response of Photosynthesis, Metabolism, and Growth to an Increase in Irradiance in the Photosynthetic Model Organism Chlamydomonas reinhardtii

    Tabea Mettler;Timo Mühlhaus;Dorothea Hemme;Mark-Aurel Schöttler

  • Protein-protein interactions and metabolite channelling in the plant tricarboxylic acid cycle

    Youjun Zhang;Katherine F. M. Beard;Corné Swart;Susan Bergmann

  • Bottom-up Metabolic Reconstruction of Arabidopsis and Its Application to Determining the Metabolic Costs of Enzyme Production

    Anne Arnold;Zoran Nikoloski

  • Inner composition alignment for inferring directed networks from short time series.

    S. Hempel;A. Koseska;J. Kurths;J. Kurths;Z. Nikoloski

  • Decreased Nucleotide and Expression Diversity and Modified Coexpression Patterns Characterize Domestication in the Common Bean

    Elisa Bellucci;Elena Bitocchi;Alberto Ferrarini;Andrea Benazzo

  • Metabolic profiling of a mapping population exposes new insights in the regulation of seed metabolism and seed, fruit, and plant relations.

    David Toubiana;Yaniv Semel;Takayuki Tohge;Romina Beleggia

Frequent Co-Authors

Alisdair R. Fernie
Alisdair R. Fernie Max Planck Institute of Molecular Plant Physiology
Joachim Selbig
Joachim Selbig Max Planck Society
Takayuki Tohge
Takayuki Tohge Nara Institute of Science and Technology
Lothar Willmitzer
Lothar Willmitzer Max Planck Society
Staffan Persson
Staffan Persson University of Copenhagen
Mark Stitt
Mark Stitt Max Planck Institute of Molecular Plant Physiology
Yariv Brotman
Yariv Brotman Tel Aviv University
Bernd Mueller-Roeber
Bernd Mueller-Roeber University of Potsdam
Saleh Alseekh
Saleh Alseekh Max Planck Society
Wagner L. Araújo
Wagner L. Araújo Universidade Federal de Viçosa

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