World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
12790
World Ranking
5792
National Ranking
2631

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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