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DeepNOE: Leveraging deep learning for protein structure solving at ultra-high resolution on the basis of NMR measurements with exact nuclear Overhauser enhancement

Project description

Ultra-high resolution protein structure on the basis of NMR measurements

Nuclear magnetic resonance (NMR) spectroscopy is essential for protein structure analysis allowing the measurement of the dynamics and structure of a protein under nearly physiological conditions. Recent studies on exact nuclear Overhauser enhancements (eNOEs) have enabled distance measurements in proteins by NMR with an accuracy of 0.1 Å. The EU-funded DeepNOE project aims to develop the innovative model/algorithm that automatically transforms raw NMR measurements into high-resolution protein structures that reveal multiple simultaneously populated conformational states in atomic detail. The study will include the application of deep learning, a novel field in machine learning that has revolutionised data science and artificial intelligence.

Field of science

  • /natural sciences/chemical sciences/analytical chemistry/spectroscopy
  • /natural sciences/biological sciences/biochemistry/biomolecules/proteins
  • /natural sciences/biological sciences/molecular biology/structural biology
  • /natural sciences/computer and information sciences/data science
  • /natural sciences/computer and information sciences/artificial intelligence/machine learning/deep learning

Call for proposal

H2020-MSCA-IF-2019
See other projects for this call

Funding Scheme

MSCA-IF-EF-ST - Standard EF

Coordinator

EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Address
Raemistrasse 101
8092 Zuerich
Switzerland
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 191 149,44