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

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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