World's Best Scientists 2026 revealed!

D-Index & Metrics

Biology and Biochemistry

D-Index
65
Citations
23401
World Ranking
8970
National Ranking
3985

Nathan E. Lewis 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 Nathan E. Lewis 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: 248 publications — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Nathan E. Lewis 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 Nathan E. Lewis 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: 65 D-Index — 55th percentile

55% of scientists in this discipline score the same or lower.

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

Overview

Nathan E. Lewis is affiliated with the University of California, San Diego in the United States. Their research primarily spans the field of Biochemistry, Genetics and Molecular Biology, with a strong focus on several interconnected subfields such as Molecular Biology, Genetics, Immunology, Cell Biology, and Radiology, Nuclear Medicine and Imaging.

The research topics covered by Nathan E. Lewis include Viral Infectious Diseases and Gene Expression in Insects, Microbial Metabolic Engineering and Bioproduction, Glycosylation and Glycoproteins Research, CRISPR and Genetic Engineering, Gene Regulatory Network Analysis, Single-cell and spatial transcriptomics, and Monoclonal and Polyclonal Antibodies Research.

Recent papers authored or co-authored by Nathan E. Lewis include the following:

  • Deciphering cell-cell interactions and communication from gene expression (2020, Nature Reviews Genetics)
  • MEMOTE for standardized genome-scale metabolic model testing (2020, Nature Biotechnology)
  • Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor (2020, Cell Host & Microbe)
  • Prenatal Origins of ASD: The When, What, and How of ASD Development (2020, Trends in Neurosciences)
  • What are housekeeping genes? (2022, PLoS Computational Biology)

Nathan E. Lewis has collaborated frequently with a number of co-authors, including Austin W.T. Chiang, Benjamin P. Kellman, Erick Armingol, Hooman Hefzi, and Hratch Baghdassarian.

Their work has been published in multiple venues, with the most frequent including bioRxiv (Cold Spring Harbor Laboratory), Metabolic Engineering, The FASEB Journal, Nature Communications, and the Journal of Allergy and Clinical Immunology.

Best Publications

  • Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

    Jan Schellenberger;Richard Que;Ronan M T Fleming;Ines Thiele

  • Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

    Laurent Heirendt;Sylvain Arreckx;Thomas Pfau;Sebastián N. Mendoza

  • BiGG Models: A platform for integrating, standardizing and sharing genome-scale models.

    Zachary A. King;Justin Lu;Andreas Dräger;Andreas Dräger;Philip Miller

  • Constraining the metabolic genotype–phenotype relationship using a phylogeny of in silico methods

    Nathan E. Lewis;Harish Nagarajan;Bernhard O. Palsson

  • The genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line

    Xun Xu;Harish Nagarajan;Nathan E Lewis;Shengkai Pan

  • Deciphering cell-cell interactions and communication from gene expression.

    Erick Armingol;Adam Officer;Olivier Harismendy;Nathan E Lewis

  • Omic data from evolved E. coli are consistent with computed optimal growth from genome‐scale models

    Nathan E Lewis;Kim K Hixson;Tom M Conrad;Joshua A Lerman

  • Design and analysis of synthetic carbon fixation pathways.

    Arren Bar-Even;Elad Noor;Nathan E. Lewis;Nathan E. Lewis;Ron Milo

  • MEMOTE for standardized genome-scale metabolic model testing

    Christian Lieven;Moritz Emanuel Beber;Brett G. Olivier;Frank T. Bergmann

  • Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor.

    Peng Zhao;Jeremy L. Praissman;Oliver C. Grant;Yongfei Cai

  • Genomic landscapes of Chinese hamster ovary cell lines as revealed by the Cricetulus griseus draft genome

    Nathan E Lewis;Xin Liu;Yuxiang Li;Harish Nagarajan

  • An enhanced CRISPR repressor for targeted mammalian gene regulation

    Nan Cher Yeo;Alejandro Chavez;Alissa Lance-Byrne;Yingleong Chan;Yingleong Chan

  • Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways.

    Zachary A. King;Andreas Dräger;Ali Ebrahim;Nikolaus Sonnenschein

  • Combinatorial CRISPR–Cas9 screens for de novo mapping of genetic interactions

    John Paul Shen;Dongxin Zhao;Roman Sasik;Jens Luebeck

  • Recon 2.2: from reconstruction to model of human metabolism

    Neil Swainston;Kieran Smallbone;Hooman Hefzi;Paul D. Dobson

  • Microbial laboratory evolution in the era of genome‐scale science

    Tom M Conrad;Nathan E Lewis;Bernhard Ø Palsson

  • The role of replicates for error mitigation in next-generation sequencing.

    Kimberly Robasky;Nathan E. Lewis;George M. Church

  • In silico method for modelling metabolism and gene product expression at genome scale

    Joshua A. Lerman;Daniel R. Hyduke;Haythem Latif;Vasiliy A. Portnoy

  • Network context and selection in the evolution to enzyme specificity

    Hojung Nam;Nathan E. Lewis;Nathan E. Lewis;Joshua A. Lerman;Dae-Hee Lee

  • Large-scale in silico modeling of metabolic interactions between cell types in the human brain

    Nathan E. Lewis;Gunnar Schramm;Gunnar Schramm;Aarash Bordbar;Jan Schellenberger

Frequent Co-Authors

Bernhard O. Palsson
Bernhard O. Palsson University of California, San Diego
Gyun Min Lee
Gyun Min Lee Korea Advanced Institute of Science and Technology
Eric Courchesne
Eric Courchesne University of California, San Diego
Michael V. Lombardo
Michael V. Lombardo Italian Institute of Technology
Dong-Yup Lee
Dong-Yup Lee Sungkyunkwan University
Lars K. Nielsen
Lars K. Nielsen University of Queensland
Jeffrey D. Esko
Jeffrey D. Esko University of California, San Diego
Michael J. Betenbaugh
Michael J. Betenbaugh Johns Hopkins University
Jens Nielsen
Jens Nielsen Chalmers University of Technology
Karen Pierce
Karen Pierce University of California, San Diego

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