World's Best Scientists 2026 revealed!
William Stafford Noble

William Stafford Noble

D-Index & Metrics

Biology and Biochemistry

D-Index
112
Citations
91077
World Ranking
877
National Ranking
548

Computer Science

D-Index
104
Citations
92216
World Ranking
293
National Ranking
161

William Stafford Noble 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 William Stafford Noble 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: 339 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

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

William Stafford Noble 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 William Stafford Noble 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: 104 D-Index — 98th percentile

98% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2001 - Fellow of Alfred P. Sloan Foundation

Overview

William Stafford Noble is affiliated with the University of Washington in the United States. Their research primarily spans the fields of Biochemistry, Genetics and Molecular Biology, with significant work also in Chemistry. Subfields of study include Molecular Biology, Spectroscopy, Biophysics, Genetics, and Plant Science.

The scientist's main research topics focus on advanced techniques and applications in proteomics and mass spectrometry, as well as genomic and chromatin dynamics. Additional topics include single-cell and spatial transcriptomics, metabolomics and mass spectrometry studies, RNA research and splicing, and genomics and phylogenetic studies.

William Stafford Noble has published extensively, with frequent coauthors including Uri Keich, William E. Fondrie, Jacob Schreiber, Jay Shendure, and Michael J. MacCoss. Their work appears regularly in several prominent publication venues:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of Proteome Research
  • Nature Communications
  • Bioinformatics
  • Genome biology

Notable recent papers authored or coauthored by Noble include:

  • "Navigating the pitfalls of applying machine learning in genomics" (2021, Nature Reviews Genetics)
  • "Systematic reconstruction of cellular trajectories across mouse embryogenesis" (2022, Nature Genetics)
  • "A High-Throughput Screen for Transcription Activation Domains Reveals Their Sequence Features and Permits Prediction by Deep Learning" (2020, Molecular Cell)
  • "A single-cell time-lapse of mouse prenatal development from gastrula to birth" (2024, Nature)
  • "Avocado: a multi-scale deep tensor factorization method learns a latent representation of the human epigenome" (2020, Genome biology)

William Stafford Noble was awarded the Fellow of Alfred P. Sloan Foundation in 2001.

Best Publications

  • MEME Suite: tools for motif discovery and searching

    Timothy L. Bailey;Mikael Bodén;Fabian A. Buske;Martin C. Frith

  • Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project

    Ewan Birney;John A. Stamatoyannopoulos;Anindya Dutta;Roderic Guigó

  • The MEME Suite

    Timothy L. Bailey;James Johnson;Charles E. Grant;William S. Noble

  • FIMO: scanning for occurrences of a given motif.

    Charles E. Grant;Timothy L. Bailey;William Stafford Noble

  • What is a support vector machine

    William S Noble

  • The ENCODE (ENCyclopedia of DNA elements) Project

    E. A. Feingold;P. J. Good;M. S. Guyer;S. Kamholz

  • An integrated encyclopedia of DNA elements in the human genome

    Ian Dunham;Anshul Kundaje;Shelley F. Aldred;Patrick J. Collins

  • Semi-supervised learning for peptide identification from shotgun proteomics datasets

    Lukas Käll;Jesse D Canterbury;Jason Weston;William Stafford Noble

  • Expanded encyclopaedias of DNA elements in the human and mouse genomes

    Jill E. Moore;Michael J. Purcaro;Henry E. Pratt;Charles B. Epstein

  • Quantifying similarity between motifs

    Shobhit Gupta;John A Stamatoyannopoulos;Timothy L Bailey;William Stafford Noble

  • Machine learning applications in genetics and genomics

    Maxwell W. Libbrecht;William Stafford Noble

  • Assessing computational tools for the discovery of transcription factor binding sites.

    Martin Tompa;Nan Li;Timothy L. Bailey;George M. Church

  • A User's Guide to the Encyclopedia of DNA Elements (ENCODE)

    Richard M. Myers;John Stamatoyannopoulos;Michael Snyder;Ian Dunham

  • The spectrum kernel: a string kernel for SVM protein classification.

    Christina S. Leslie;Eleazar Eskin;William Stafford Noble

  • A three-dimensional model of the yeast genome

    Zhijun Duan;Mirela Andronescu;Kevin Schutz;Sean McIlwain

  • Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors.

    Jie Wang;Jiali Zhuang;Sowmya Iyer;Sowmya Iyer;XinYing Lin

  • Mismatch string kernels for discriminative protein classification

    Christina S. Leslie;Eleazar Eskin;Adiel Cohen;Jason Weston

  • How does multiple testing correction work

    William Stafford Noble

  • A statistical framework for genomic data fusion

    Gert R. G. Lanckriet;Tijl De Bie;Nello Cristianini;Michael I. Jordan

  • Integrative annotation of chromatin elements from ENCODE data

    Michael M. Hoffman;Jason Ernst;Jason Ernst;Jason Ernst;Steven P. Wilder;Anshul Kundaje;Anshul Kundaje

  • A three-dimensional model of the yeast genome

    William Noble;Zhi-un Duan;Mirela Andronescu;Kevin Schutz

  • The spectrum kernel

    Christina Leslie;Eleazar Eskin;William Stafford Noble

Frequent Co-Authors

Jeff A. Bilmes
Jeff A. Bilmes University of Washington
Jay Shendure
Jay Shendure University of Washington
Ferhat Ay
Ferhat Ay La Jolla Institute For Allergy & Immunology
Jean-Philippe Vert
Jean-Philippe Vert Google (United States)
Michael J. MacCoss
Michael J. MacCoss University of Washington
Christina S. Leslie
Christina S. Leslie Memorial Sloan Kettering Cancer Center
Christine M. Disteche
Christine M. Disteche University of Washington
Jason Weston
Jason Weston Facebook (United States)
John A. Stamatoyannopoulos
John A. Stamatoyannopoulos University of Washington
Job Dekker
Job Dekker University of Massachusetts Chan Medical School

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