World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
12790
World Ranking
5793
National Ranking
2632

Marshall Bern publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Marshall Bern sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 138 publications — 22nd percentile

22% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Marshall Bern D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Marshall Bern sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 49 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Marshall Bern is affiliated with Protein Metrics in the United States and has a research portfolio spanning biochemistry, genetics, molecular biology, and chemistry. Their work encompasses molecular biology, spectroscopy, genetics, food science, and animal science and zoology as subfields of study. The primary focus of their research includes advanced proteomics techniques and applications, glycosylation and glycoproteins research, genomics and phylogenetic studies, bacterial genetics and biotechnology, mass spectrometry techniques and applications, RNA and protein synthesis mechanisms, as well as fermentation and sensory analysis.

Their frequent coauthors include Cassandra L. Pegg, Toan K. Phung, Benjamin L. Schulz, Doron Kletter, and Ankur Patel. Publication venues where their work has appeared multiple times include the Journal of the American Society for Mass Spectrometry, bioRxiv (Cold Spring Harbor Laboratory), Nature Methods, Molecular & Cellular Proteomics, and Nature Microbiology.

Notable recent papers authored or coauthored by Marshall Bern include:

  • Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis (2021, Nature Methods)
  • β-Barrel proteins tether the outer membrane in many Gram-negative bacteria (2020, Nature Microbiology)
  • Peak Filtering, Peak Annotation, and Wildcard Search for Glycoproteomics (2020, Molecular & Cellular Proteomics)
  • Ultraviolet Photodissociation and Activated Electron Photodetachment Mass Spectrometry for Top-Down Sequencing of Modified Oligoribonucleotides (2022, Journal of the American Society for Mass Spectrometry)
  • PGFinder, a novel analysis pipeline for the consistent, reproducible, and high-resolution structural analysis of bacterial peptidoglycans (2021, eLife)

Best Publications

  • Surface Reconstruction by Voronoi Filtering

    Nina Amenta;Marshall W. Bern

  • A new Voronoi-based surface reconstruction algorithm

    Nina Amenta;Marshall Bern;Manolis Kamvysselis

  • MESH GENERATION AND OPTIMAL TRIANGULATION

    Marshall Bern;David Eppstein

  • Byonic: Advanced Peptide and Protein Identification Software

    Marshall Bern;Yong J. Kil;Christopher Becker

  • The crust and the B-Skeleton: combinatorial curve reconstruction

    Nina Amenta;Marshall Bern;David Eppstein

  • Provably good mesh generation

    M. Bern;D. Eppstein;J. Gilbert

  • The steiner problem with edge lengths 1 and 2

    Marshall Bern;Paul Plassmann

  • Linear-time computation of optimal subgraphs of decomposable graphs

    M. W. Bern;E. L. Lawler;A. L. Wong

  • Optimal Point Placement for Mesh Smoothing

    Nina Amenta;Marshall Bern;David Eppstein

  • Automatic Quality Assessment of Peptide Tandem Mass Spectra

    Marshall Bern;David Goldberg;W. Hayes Mcdonald;John R. Yates

  • Lookup peaks: a hybrid of de novo sequencing and database search for protein identification by tandem mass spectrometry.

    Marshall Bern;Yuhan Cai;David Goldberg

  • Approximation algorithms for geometric problems

    Marshall Bern;David Eppstein

  • SecLEACH - A Random Key Distribution Solution for Securing Clustered Sensor Networks

    L.B. Oliveira;H.C. Wong;M. Bern;R. Dahab

  • The complexity of flat origami

    Marshall Bern;Barry Hayes

  • A global approach to automatic solution of jigsaw puzzles

    David Goldberg;Christopher Malon;Marshall Bern

  • SecLEACH-On the security of clustered sensor networks

    Leonardo B. Oliveira;Adrian Ferreira;Marco A. Vilaça;Hao Chi Wong

  • Automatic particle selection: Results of a comparative study

    Yuanxin Zhu;Bridget Carragher;Robert M. Glaeser;Denis Fellmann

  • Support-Graph Preconditioners

    Marshall Bern;John R. Gilbert;Bruce Hendrickson;Nhat Nguyen

  • The Shortest-Network Problem

    Marshall W. Bern;Ronald L. Graham

  • Linear-size nonobtuse triangulation of polygons

    M. Bern;S. Michell;J. Ruppert

Frequent Co-Authors

David Eppstein
David Eppstein University of California, Irvine
Nina Amenta
Nina Amenta University of California, Davis
David P. Dobkin
David P. Dobkin Princeton University
Daniel H. Greene
Daniel H. Greene Palo Alto Research Center
John R. Yates
John R. Yates Scripps Research Institute
Herbert Edelsbrunner
Herbert Edelsbrunner Institute of Science and Technology Austria
Emiliano De Cristofaro
Emiliano De Cristofaro University of California, Riverside
Beatrix Ueberheide
Beatrix Ueberheide New York University
Jack Snoeyink
Jack Snoeyink University of North Carolina at Chapel Hill
Shang-Hua Teng
Shang-Hua Teng University of Southern California

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