World's Best Scientists 2026 revealed!

D-Index & Metrics

Biology and Biochemistry

D-Index
54
Citations
154232
World Ranking
15318
National Ranking
6387

Mark A. DePristo 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 Mark A. DePristo 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: 76 publications — 1st percentile

1% of scientists in this discipline score the same or lower.

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

Mark A. DePristo 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 Mark A. DePristo 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: 54 D-Index — 22nd percentile

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

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

Overview

Mark A. DePristo is affiliated with BigHat Biosciences in the United States and conducts research primarily in the field of Biochemistry, Genetics, and Molecular Biology. Their specialization includes subfields such as Molecular Biology, Genetics, Spectroscopy, and Cancer Research.

Their research work spans multiple topics, focusing on:

  • Genomics and Phylogenetic Studies
  • Machine Learning in Bioinformatics
  • Advanced Proteomics Techniques and Applications
  • Genomics and Rare Diseases
  • Genomic variations and chromosomal abnormalities
  • Cancer Genomics and Diagnostics

Mark A. DePristo has contributed to several key publications. Recent papers include:

  • Using deep learning to annotate the protein universe, 2022, Nature Biotechnology
  • Challenges of Accuracy in Germline Clinical Sequencing Data, 2021, JAMA

Frequent co-authors collaborating with Mark A. DePristo are:

  • Maxwell L. Bileschi
  • David Belanger
  • Drew Bryant
  • Theo Sanderson
  • Brandon Carter

The main publication venues for their work include:

  • Nature Biotechnology
  • JAMA

Best Publications

  • The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data

    Aaron Henrik McKenna;Matthew Hanna;Eric Banks;Andrey Sivachenko

  • A global reference for human genetic variation.

    Adam Auton;Gonçalo R. Abecasis;David M. Altshuler;Richard M. Durbin

  • The variant call format and VCFtools

    Petr Danecek;Adam Auton;Goncalo Abecasis;Cornelis A. Albers

  • An integrated map of genetic variation from 1,092 human genomes

    Goncalo R Abecasis;Adam Auton;Lisa D Brooks

  • A framework for variation discovery and genotyping using next-generation DNA sequencing data

    Mark A DePristo;Eric Banks;Ryan Poplin;Kiran V Garimella

  • Analysis of protein-coding genetic variation in 60,706 humans

    Monkol Lek;Konrad J. Karczewski;Konrad J. Karczewski;Eric V. Minikel;Eric V. Minikel;Kaitlin E. Samocha

  • Table S2: Trans-factors and trinucleotide repeat instability Trans-factor

    Arturo López Castel;John D Cleary;Christopher E Pearson

  • From FastQ Data to High‐Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline

    Geraldine A. Van der Auwera;Mauricio O. Carneiro;Christopher Hartl;Ryan Poplin

  • A guide to deep learning in healthcare.

    Andre Esteva;Alexandre Robicquet;Bharath Ramsundar;Volodymyr Kuleshov

  • Patterns and rates of exonic de novo mutations in autism spectrum disorders

    Benjamin M. Neale;Yan Kou;Li Liu;Avi Ma'Ayan

  • Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome.

    Aaron M. Wenger;Paul Peluso;William J. Rowell;Pi-Chuan Chang

  • A polygenic burden of rare disruptive mutations in schizophrenia

    Shaun M Purcell;Jennifer L Moran;Menachem Fromer;Douglas Ruderfer

  • Darwinian evolution can follow only very few mutational paths to fitter proteins.

    Daniel M. Weinreich;Nigel F. Delaney;Mark A. DePristo;Daniel L. Hartl

  • Scaling accurate genetic variant discovery to tens of thousands of samples

    Poplin R;Ruano-Rubio;DePristo Ma;Fennell Tj

  • A Systematic Survey of Loss-of-Function Variants in Human Protein-Coding Genes

    Daniel G. MacArthur;Daniel G. MacArthur;Suganthi Balasubramanian;Adam Frankish;Ni Huang

  • Mapping copy number variation by population-scale genome sequencing

    Ryan E. Mills;Klaudia Walter;Chip Stewart;Robert E. Handsaker

  • A universal SNP and small-indel variant caller using deep neural networks.

    Ryan Poplin;Pi-Chuan Chang;David Alexander;Scott Schwartz

  • The genetic architecture of type 2 diabetes

    Christian Fuchsberger;Christian Fuchsberger;Jason A. Flannick;Jason A. Flannick;Tanya M. Teslovich;Anubha Mahajan

  • A framework for the interpretation of de novo mutation in human disease

    Kaitlin E Samocha;Elise B Robinson;Stephan J Sanders;Christine Stevens

  • Sublethal Antibiotic Treatment Leads to Multidrug Resistance via Radical-Induced Mutagenesis

    Michael A. Kohanski;Mark A. DePristo;James J. Collins

Frequent Co-Authors

David Altshuler
David Altshuler Harvard University
Mark J. Daly
Mark J. Daly Massachusetts General Hospital
Eric Banks
Eric Banks Broad Institute
Stacey Gabriel
Stacey Gabriel Broad Institute
Shaun Purcell
Shaun Purcell Harvard Medical School
Benjamin M. Neale
Benjamin M. Neale Harvard University
Jason Flannick
Jason Flannick Broad Institute
Andrew P. Morris
Andrew P. Morris University of Liverpool
Gonçalo R. Abecasis
Gonçalo R. Abecasis University of Michigan–Ann Arbor
Daniel G. MacArthur
Daniel G. MacArthur Garvan Institute of Medical Research

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