World's Best Scientists 2026 revealed!

D-Index & Metrics

Biology and Biochemistry

D-Index
59
Citations
18312
World Ranking
12303
National Ranking
118

Michal Linial 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 Michal Linial 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: 264 publications — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Michal Linial 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 Michal Linial 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: 59 D-Index — 38th percentile

38% of scientists in this discipline score the same or lower.

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

Overview

Michal Linial is affiliated with the Hebrew University of Jerusalem in Israel. Their research contributions span diverse areas within biochemistry, genetics, molecular biology, and medicine, with a strong focus on molecular biology, cancer research, genetics, infectious diseases, and neurology.

Their recent scholarly output includes publications across multiple venues and topics. Notable recent papers include:

  • ProteinBERT: a universal deep-learning model of protein sequence and function, 2022, Bioinformatics
  • The language of proteins: NLP, machine learning & protein sequences, 2021, Computational and Structural Biotechnology Journal
  • The SARS-CoV-2 Exerts a Distinctive Strategy for Interacting with the ACE2 Human Receptor, 2020, Viruses
  • PWAS: proteome-wide association study-linking genes and phenotypes by functional variation in proteins, 2020, Genome Biology
  • Open problems in human trait genetics, 2022, Genome Biology

Michal Linial's work intersects multiple research themes. The main topics they have addressed include:

  • Genetic associations and epidemiology
  • Cancer-related molecular mechanisms research
  • Bioinformatics and genomic networks
  • Epigenetics and DNA methylation
  • MicroRNA in disease regulation
  • Neuroinflammation and neurodegeneration mechanisms
  • RNA and protein synthesis mechanisms

The scientist frequently coauthors with a number of researchers in their field. Frequent collaborators include:

  • Keren Zohar
  • Nadav Brandes
  • Dan Ofer
  • Tsiona Eliyahu
  • Roei Zucker

Publications by Michal Linial are often featured in venues that support rapid dissemination of findings, including:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Preprints.org
  • Research Square
  • International Journal of Molecular Sciences
  • Vaccines

The breadth of their work is reflected in the distribution of publications across main fields of study, predominantly Biochemistry, Genetics and Molecular Biology with 193 publications, followed by Medicine with 74. Subfields emphasize Molecular Biology with 105 papers, Cancer Research at 44, Genetics at 37, Infectious Diseases and Neurology each with 18 publications. The spectrum illustrates a strong interdisciplinary approach combining experimental biology with computational methods.

Best Publications

  • Using Bayesian networks to analyze expression data

    Nir Friedman;Michal Linial;Iftach Nachman;Dana Pe'er

  • Insights into social insects from the genome of the honeybee Apis mellifera

    George M. Weinstock;Gene E. Robinson;Richard A. Gibbs;Kim C. Worley

  • A large-scale evaluation of computational protein function prediction

    Predrag Radivojac;Wyatt T Clark;Tal Ronnen Oron;Alexandra M Schnoes

  • ProteinBERT: A universal deep-learning model of protein sequence and function

    Dan Ofer;Nadav Brandes;Michal Linial;Nadav Rappoport

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

  • The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

    Naihui Zhou;Yuxiang Jiang;Timothy R. Bergquist;Alexandra J. Lee

  • Vesicular neurotransmitter transporters: from bacteria to humans.

    S Schuldiner;A Shirvan;M Linial

  • Novel Unsupervised Feature Filtering of Biological Data

    Roy Varshavsky;Assaf Gottlieb;Michal Linial;David Horn

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T Clark;Asma R Bankapur

  • Protein function annotation by homology-based inference

    Yaniv Loewenstein;Domenico Raimondo;Oliver C Redfern;James Watson

  • Viral adaptation to host: a proteome-based analysis of codon usage and amino acid preferences.

    Iris Bahir;Menachem Fromer;Yosef Prat;Michal Linial

  • The language of proteins: NLP, machine learning & protein sequences.

    Dan Ofer;Nadav Brandes;Michal Linial

  • Brain contains two forms of synaptic vesicle protein 2.

    Sandra M. Bajjalieh;Karen Peterson;Michal Linial;Richard H. Scheller

  • ProtoMap: automatic classification of protein sequences and hierarchy of protein families

    Golan Yona;Nathan Linial;Michal Linial

  • Polysaccharide-oligoamine based conjugates for gene delivery.

    Tony Azzam;Hagit Eliyahu;Libi Shapira;Michal Linial

  • Cellular and molecular biology of the presynaptic nerve terminal.

    W S Trimble;M Linial;R H Scheller

  • Nonlinear optical measurement of membrane potential around single molecules at selected cellular sites.

    Gadi Peleg;Aaron Lewis;Michal Linial;Leslie M. Loew

  • Efficient algorithms for accurate hierarchical clustering of huge datasets

    Yaniv Loewenstein;Elon Portugaly;Menachem Fromer;Michal Linial

  • The SARS-CoV-2 Exerts a Distinctive Strategy for Interacting with the ACE2 Human Receptor.

    Esther S. Brielle;Dina Schneidman-Duhovny;Michal Linial

  • Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

Frequent Co-Authors

Nathan Linial
Nathan Linial Hebrew University of Jerusalem
Burkhard Rost
Burkhard Rost Technical University of Munich
Menachem Fromer
Menachem Fromer Broad Institute
Christophe Dessimoz
Christophe Dessimoz University College London
Daisuke Kihara
Daisuke Kihara Purdue University West Lafayette
David T. Jones
David T. Jones University College London
Tapio Salakoski
Tapio Salakoski University of Turku
Predrag Radivojac
Predrag Radivojac Northeastern University
Thomas Lengauer
Thomas Lengauer Max Planck Institute for Informatics
Pardis C. Sabeti
Pardis C. Sabeti Harvard University

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