Burkhard Rost

Affiliated Professor

Technical University of Munich

Germany

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About

Burkhard Rost is an Affiliated Professor at the Technical University of Munich, Germany. His research focuses on the intersection of artificial intelligence and protein science, as evidenced by his recent publications on protein language models and competitive binding prediction. His work seeks to advance the understanding of protein interactions and enhance predictive capabilities within the field.

Articles (13)

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2025

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2022

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2022

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2022

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2022

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2022

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2022

Collaborators (16)

Jordan Ramilowski

Professor

Yokohama National University

JAPAN

Burkhard Rost

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Articles (13)

Teaching AI to speak protein

bindNode24: Competitive binding residue prediction with 60 % smaller model

Fine-tuning protein language models boosts predictions across diverse tasks

Novel machine learning approaches revolutionize protein knowledge

LambdaPP: Fast and accessible protein-specific phenotype predictions

CATHe: detection of remote homologues for CATH superfamilies using embeddings from protein language models

Engineering indel and substitution variants of diverse and ancient enzymes using Graphical Representation of Ancestral Sequence Predictions (GRASP)

Author Correction: Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network (Nature Communications, (2021), 12, 1, (3297), 10.1038/s41467-021-23143-7)

ProteomicsDB: toward a FAIR open-source resource for life-science research.

Contrastive learning on protein embeddings enlightens midnight zone

Embeddings from protein language models predict conservation and variant effects

ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning

Protein language-model embeddings for fast, accurate, and alignment-free protein structure prediction

Collaborators (16)

Jordan Ramilowski

Martin Steinegger

Christine Orengo

Hozumi Motohashi

Gerhard Schenk

ELIZABETH GILLAM

Leander Sützl

Christian Dallago

Matthew The

Leonard Lipovich

Alka Saxena

Bostjan Kobe

Nicola Bordin

Louise Winteringham

Taku Hatano

Tony Kenna

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bindNode24: Competitive binding residue prediction with 60 % smaller model