World's Best Scientists 2026 revealed!
Gisbert Schneider

Gisbert Schneider

Award Badge
Engineering and Technology
Switzerland
2026

D-Index & Metrics

Chemistry

D-Index
86
Citations
31987
World Ranking
2495
National Ranking
59

Engineering and Technology

D-Index
84
Citations
30712
World Ranking
409
National Ranking
6

Research.com Recognitions

  • 2026 - Research.com Engineering and Technology in Switzerland Leader Award
  • 2025 - Research.com Engineering and Technology in Switzerland Leader Award

Overview

Gisbert Schneider is affiliated with ETH Zurich in Switzerland and specializes in research at the intersection of computer science and molecular biology. Their work spans core fields including Computational Theory and Mathematics, Molecular Biology, Materials Chemistry, Organic Chemistry, and Pharmacology.

Their primary research topics focus heavily on computational drug discovery methods, encompassing machine learning applications in materials science, protein structure and dynamics, chemical synthesis and analysis, microbial natural products and biosynthesis, synthesis and biological activity, and genetics, bioinformatics, and biomedical research.

Schneider's recent published papers include:

  • Artificial intelligence in drug discovery: recent advances and future perspectives (2021), published in Expert Opinion on Drug Discovery
  • Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR (2023), published in Nature Reviews Drug Discovery
  • Bidirectional Molecule Generation with Recurrent Neural Networks (2020), published in Journal of Chemical Information and Modeling
  • Generative molecular design in low data regimes (2020), published in Nature Machine Intelligence
  • A critical overview of computational approaches employed for COVID-19 drug discovery (2021), published in Chemical Society Reviews

Frequent collaborators have included Kenneth Atz, Francesca Grisoni, Clemens Isert, Petra Schneider, and Cyrill Brunner. These co-authorships highlight active cooperation within teams specializing in computational drug design and related areas.

Common venues for Schneider's publications reflect this interdisciplinary focus, with multiple contributions in:

  • Nature Machine Intelligence
  • Molecular Informatics
  • Chemical Biology & Drug Design
  • Journal of Chemical Information and Modeling
  • Nature Communications

Schneider's expertise lies predominantly in computer science and biochemistry-related disciplines, with a substantial number of publications contributing to both the theoretical and applied aspects of drug discovery and molecular informatics.

Best Publications

  • Counting on natural products for drug design

    Tiago Rodrigues;Daniel Reker;Petra Schneider;Gisbert Schneider

  • Computer-based de novo design of drug-like molecules

    Gisbert Schneider;Uli Fechner

  • Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery

    Xin Yang;Yifei Wang;Ryan Byrne;Gisbert Schneider

  • “Scaffold-Hopping” by Topological Pharmacophore Search: A Contribution to Virtual Screening

    Gisbert Schneider;Werner Neidhart;Thomas Giller;Gerard Schmid

  • Automating drug discovery

    Gisbert Schneider

  • Rethinking drug design in the artificial intelligence era

    Petra Schneider;W. Patrick Walters;Alleyn T. Plowright;Norman Sieroka

  • Drug discovery with explainable artificial intelligence

    José Jiménez-Luna;Francesca Grisoni;Gisbert Schneider

  • Comparison of Support Vector Machine and Artificial Neural Network Systems for Drug/Nondrug Classification

    Evgeny Byvatov;Uli Fechner;Jens Sadowski;Gisbert Schneider

  • Deep Learning in Drug Discovery.

    Erik Gawehn;Jan A. Hiss;Gisbert Schneider

  • Virtual screening: an endless staircase?

    Gisbert Schneider

  • Virtual screening and fast automated docking methods.

    Gisbert Schneider;Hans-Joachim Böhm

  • Predicting drug metabolism: experiment and/or computation?

    Johannes Kirchmair;Andreas H Göller;Dieter Lang;Jens Kunze

  • Generative Recurrent Networks for De Novo Drug Design.

    Anvita Gupta;Anvita Gupta;Alex T. Müller;Berend J. H. Huisman;Jens A. Fuchs

  • PocketPicker: analysis of ligand binding-sites with shape descriptors

    Martin Weisel;Ewgenij Proschak;Gisbert Schneider

  • Support vector machine applications in bioinformatics.

    Evgeny Byvatov;Gisbert Schneider

  • Artificial intelligence in drug discovery: recent advances and future perspectives.

    José Jiménez-Luna;Francesca Grisoni;Nils Weskamp;Gisbert Schneider

  • Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training

    Michael Meissner;Michael Schmuker;Gisbert Schneider

  • Scaffold architecture and pharmacophoric properties of natural products and trade drugs: application in the design of natural product-based combinatorial libraries.

    Man-Ling Lee;Gisbert Schneider

  • De Novo Design of Bioactive Small Molecules by Artificial Intelligence

    Daniel Merk;Lukas Friedrich;Francesca Grisoni;Francesca Grisoni;Gisbert Schneider

  • De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks.

    Gisbert Schneider;Man-Ling Lee;Martin Stahl;Petra Schneider

  • Development of a virtual screening method for identification of "frequent hitters" in compound libraries.

    Olivier Roche;Petra Schneider;Jochen Zuegge;Wolfgang Guba

  • Artificial neural networks for computer-based molecular design.

    Gisbert Schneider;Paul Wrede

Frequent Co-Authors

Matthias Rupp
Matthias Rupp Luxembourg Institute of Science and Technology
Steffen Backert
Steffen Backert University of Erlangen-Nuremberg
Gerd Geisslinger
Gerd Geisslinger Goethe University Frankfurt
Tanja Weil
Tanja Weil Max Planck Society
Herbert Waldmann
Herbert Waldmann Max Planck Society
Klaus-Robert Müller
Klaus-Robert Müller Technical University of Berlin
Ulrike Koehl
Ulrike Koehl Leipzig University
Peter Walden
Peter Walden Charité - University Medicine Berlin

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