World's Best Scientists 2026 revealed!
Gunnar Rätsch

Gunnar Rätsch

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Computer Science
Switzerland
2025

D-Index & Metrics

Computer Science

D-Index
77
Citations
54543
World Ranking
1228
National Ranking
31

Gunnar Rätsch 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 Gunnar Rätsch 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 254 publications — 64th percentile

64% of scientists in this discipline score the same or lower.

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

Gunnar Rätsch 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 Gunnar Rätsch sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 77 D-Index — 91st percentile

91% 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

  • 2025 - Research.com Computer Science in Switzerland Leader Award
  • 2022 - Research.com Computer Science in Switzerland Leader Award

Overview

Gunnar Rätsch is affiliated with ETH Zurich in Switzerland, contributing extensively to the fields of Biochemistry, Genetics and Molecular Biology as well as Computer Science. Their research spans several key subfields including Molecular Biology, Artificial Intelligence, Cancer Research, Computer Vision and Pattern Recognition, and Epidemiology.

The main topics covered in Gunnar Rätsch's work include:

  • Genomics and Phylogenetic Studies
  • Machine Learning in Healthcare
  • Cancer Genomics and Diagnostics
  • Single-cell and Spatial Transcriptomics
  • Algorithms and Data Compression
  • RNA Modifications and Cancer
  • Sepsis Diagnosis and Treatment

Gunnar Rätsch has contributed to a number of recent publications, demonstrating a focus on healthcare applications and molecular biology, including:

  • "Early prediction of circulatory failure in the intensive care unit using machine learning" (2020) published in Nature Medicine
  • "A global metagenomic map of urban microbiomes and antimicrobial resistance" (2021) in Cell
  • "Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment" (2020) in Nature Medicine
  • "The Tumor Profiler Study: integrated, multi-omic, functional tumor profiling for clinical decision support" (2021) in Cancer Cell
  • "Learning single-cell perturbation responses using neural optimal transport" (2023) in Nature Methods

The scientist frequently collaborates with a group of coauthors including:

  • André Kahles
  • Kjong-Van Lehmann
  • Harun Mustafa
  • Ximena Bonilla
  • Stefan G. Stark

Gunnar Rätsch's work appears predominantly in several publication venues, highlighting contributions in both preprint and peer-reviewed platforms:

  • arXiv (Cornell University) with 35 publications
  • bioRxiv (Cold Spring Harbor Laboratory) with 30 publications
  • Bioinformatics with 9 publications
  • Nature Medicine with 5 publications
  • Zenodo (CERN European Organization for Nuclear Research) with 4 publications

Best Publications

  • The cancer genome atlas pan-cancer analysis project

    John N Weinstein;John N Weinstein;Eric A. Collisson;Gordon B Mills;Kenna R Mills Shaw;Kenna R Mills Shaw

  • An introduction to kernel-based learning algorithms

    K.-R. Muller;S. Mika;G. Ratsch;K. Tsuda

  • Fisher discriminant analysis with kernels

    S. Mika;G. Ratsch;J. Weston;B. Scholkopf

  • Pan-cancer analysis of whole genomes

    Peter J. Campbell;Gad Getz;Jan O. Korbel;Joshua M. Stuart

  • The Molecular Taxonomy of Primary Prostate Cancer

    Adam Abeshouse;Jaeil Ahn;Rehan Akbani;Adrian Ally

  • Large Scale Multiple Kernel Learning

    Sören Sonnenburg;Gunnar Rätsch;Christin Schäfer;Bernhard Schölkopf

  • Soft Margins for AdaBoost

    G. Rätsch;T. Onoda;K.-R. Müller

  • Input space versus feature space in kernel-based methods

    B. Scholkopf;S. Mika;C.J.C. Burges;P. Knirsch

  • Predicting Time Series with Support Vector Machines

    Klaus-Robert Müller;Alex J. Smola;Gunnar Rätsch;Bernhard Schölkopf

  • Kernel PCA and De-Noising in Feature Spaces

    Sebastian Mika;Bernhard Schölkopf;Alex J. Smola;Klaus-Robert Müller

  • Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project

    Mark B. Gerstein;Zhi John Lu;Eric L. Van Nostrand;Chao Cheng

  • Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients.

    André Kahles;Kjong-Van Lehmann;Nora C Toussaint;Matthias Hüser

  • Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations

    Francesco Locatello;Stefan Bauer;Mario Lučić;Gunnar Rätsch

  • Support vector machines and kernels for computational biology.

    Asa Ben-Hur;Cheng Soon Ong;Sören Sonnenburg;Bernhard Schölkopf

  • Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota.

    Richard R. Stein;Vanni Bucci;Nora C. Toussaint;Charlie G. Buffie

  • An introduction to boosting and leveraging

    Ron Meir;Gunnar Rätsch

  • Engineering support vector machine kernels that recognize translation initiation sites

    Alexander Zien;Gunnar Rätsch;Sebastian Mika;Bernhard Schölkopf

  • Systematic evaluation of spliced alignment programs for RNA-seq data

    Pär G Engström;Tamara Steijger;Botond Sipos;Gregory R Grant

  • Active Learning with support Vector machines in the drug discovery process

    Manfred K. Warmuth;Jun Liao;Gunnar Rätsch;Michael Mathieson

  • Advanced Lectures on Machine Learning

    O Bousquet;U von Luxburg;G Rätsch

  • Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs

    Cristóbal Esteban;Stephanie L. Hyland;Gunnar Rätsch

  • Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites.

    Alexander Zien;Gunnar Rätsch;Sebastian Mika;Bernhard Schölkopf

  • The Cancer Genome Atlas Pan-Cancer analysis project

    Kyle Chang;Chad J Creighton;Caleb Davis;Lawrence Donehower

Frequent Co-Authors

Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Klaus-Robert Müller
Klaus-Robert Müller Technical University of Berlin
Oliver Stegle
Oliver Stegle German Cancer Research Center
Mark Gerstein
Mark Gerstein Yale University
Andrea Sboner
Andrea Sboner Cornell University
Eran Segal
Eran Segal Weizmann Institute of Science
Alexander J. Smola
Alexander J. Smola Amazon (United States)
Detlef Weigel
Detlef Weigel Max Planck Institute for Developmental Biology
Michael Snyder
Michael Snyder Stanford University
Chao Cheng
Chao Cheng Baylor College of Medicine

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