Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning.

• Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable tool in chemistry and biology but often suffers from long experimental time. We present a proof-of-concept of application of deep learning and neural network for high-quality, reliable, and very fast NMR spectra reconstruction from limited experimental data. We show that the neural network training can be achieved using solely synthetic NMR signal, which lifts the prohibiting demand for large volume of realistic training data usually required in the deep learning approach.

Subject headings

NATURVETENSKAP  -- Biologi -- Strukturbiologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences -- Structural Biology (hsv//eng)

NATURVETENSKAP  -- Kemi -- Fysikalisk kemi (hsv//swe)

NATURAL SCIENCES  -- Chemical Sciences -- Physical Chemistry (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Bioinformatics (hsv//eng)

NATURVETENSKAP  -- Kemi -- Analytisk kemi (hsv//swe)

NATURAL SCIENCES  -- Chemical Sciences -- Analytical Chemistry (hsv//eng)

Publication and Content Type

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