World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
89
Citations
91915
World Ranking
623
National Ranking
11

Nir Friedman 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 Nir Friedman 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: 181 publications — 39th percentile

39% of scientists in this discipline score the same or lower.

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

Nir Friedman 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 Nir Friedman 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: 89 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

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

Overview

Nir Friedman was affiliated with the Weizmann Institute of Science in Israel. Their research spanned multiple fields, primarily focusing on Medicine and Biochemistry, Genetics and Molecular Biology. Their work delved into several subfields such as Molecular Biology, Oncology, Epidemiology, Cancer Research, and Immunology.

The scientist contributed to research on various main topics, including:

  • Cancer Genomics and Diagnostics
  • Single-cell and spatial transcriptomics
  • Epigenetics and DNA Methylation
  • Liver Disease Diagnosis and Treatment
  • Lung Cancer Research Studies
  • RNA and protein synthesis mechanisms
  • Ubiquitin and proteasome pathways

Nir Friedman published frequently in several scientific venues with notable recurring appearances in bioRxiv (Cold Spring Harbor Laboratory), Nature Biotechnology, Zenodo (CERN European Organization for Nuclear Research), Nature Communications, and the Journal of Hepatology.

Some of their recent scientific papers included the following:

  • ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells of origin, 2021, Nature Biotechnology
  • NovoSpaRc: flexible spatial reconstruction of single-cell gene expression with optimal transport, 2021, Nature Protocols
  • Extrachromosomal DNA Amplification Contributes to Small Cell Lung Cancer Heterogeneity and Is Associated with Worse Outcomes, 2023, Cancer Discovery
  • Elevated cfDNA after exercise is derived primarily from mature polymorphonuclear neutrophils, with a minor contribution of cardiomyocytes, 2023, Cell Reports Medicine
  • Selective flexible packaging pathways of the segmented genome of influenza A virus, 2020, Nature Communications

The scientist collaborated with a number of frequent co-authors throughout their career. These included Gavriel Fialkoff, Israa Sharkia, Ronen Sadeh, Jenia Gutin, and Alon Chappleboim.

Best Publications

  • Full-length transcriptome assembly from RNA-Seq data without a reference genome.

    Manfred G Grabherr;Brian J Haas;Moran Yassour;Moran Yassour;Joshua Z Levin

  • Probabilistic graphical models : principles and techniques

    Daniel L. Koller;Nir Friedman

  • De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis

    Brian J Haas;Alexie Papanicolaou;Moran Yassour;Moran Yassour;Manfred Grabherr

  • Bayesian Network Classifiers

    Nir Friedman;Dan Geiger;Moises Goldszmidt

  • Using Bayesian networks to analyze expression data

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

  • Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data

    Eran Segal;Michael Shapira;Aviv Regev;Aviv Regev;Dana Pe'er

  • Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens

    Atray Dixit;Atray Dixit;Oren Parnas;Biyu Li;Jenny Chen;Jenny Chen

  • Inferring Cellular Networks Using Probabilistic Graphical Models

    Nir Friedman

  • Paternally Induced Transgenerational Environmental Reprogramming of Metabolic Gene Expression in Mammals

    Benjamin R. Carone;Lucas Fauquier;Naomi Habib;Jeremy M. Shea

  • Image segmentation in video sequences: a probabilistic approach

    Nir Friedman;Stuart Russell

  • Tissue classification with gene expression profiles.

    Amir Ben-Dor;Laurakay Bruhn;Nir Friedman;Iftach Nachman

  • Learning Probabilistic Relational Models

    Nir Friedman;Lise Getoor;Daphne Koller;Avi Pfeffer

  • Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks

    Nir Friedman;Daphne Koller

  • Densely Interconnected Transcriptional Circuits Control Cell States in Human Hematopoiesis

    Noa Novershtern;Noa Novershtern;Noa Novershtern;Aravind Subramanian;Lee N. Lawton;Raymond H. Mak

  • Comprehensive comparative analysis of strand-specific RNA sequencing methods

    Joshua Z Levin;Moran Yassour;Moran Yassour;Xian Adiconis;Chad Nusbaum

  • A module map showing conditional activity of expression modules in cancer.

    Eran Segal;Eran Segal;Nir Friedman;Daphne Koller;Aviv Regev

  • Mapping Nucleosome Resolution Chromosome Folding in Yeast by Micro-C

    Tsung-Han S. Hsieh;Assaf Weiner;Bryan R. Lajoie;Job Dekker

  • Context-specific independence in Bayesian networks

    Craig Boutilier;Nir Friedman;Moises Goldszmidt;Daphne Koller

  • Learning bayesian network structure from massive datasets: the «sparse candidate« algorithm

    Nir Friedman;Iftach Nachman;Dana Peér

  • Inferring subnetworks from perturbed expression profiles.

    Dana Pe’er;Aviv Regev;Gal Elidan;Nir Friedman

  • Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning

    Daphne Koller;Nir Friedman

  • A Bayesian Approach to Structure Discovery in Bayesian Networks

    Nir Friedman;Daphne Koller

Frequent Co-Authors

Aviv Regev
Aviv Regev Genentech
Daphne Koller
Daphne Koller insitro Inc.
Joseph Y. Halpern
Joseph Y. Halpern Cornell University
Oliver J. Rando
Oliver J. Rando University of Massachusetts Chan Medical School
Naftali Kaminski
Naftali Kaminski Yale University
Moises Goldszmidt
Moises Goldszmidt Apple (United States)
Ido Amit
Ido Amit Weizmann Institute of Science
Nir Hacohen
Nir Hacohen Harvard University
Joshua Z. Levin
Joshua Z. Levin Broad Institute
Raz Kupferman
Raz Kupferman Hebrew University of Jerusalem

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