[NMR paper] Solution-state methyl NMR spectroscopy of large non-deuterated proteins enabled by deep neural networks
Solution-state methyl NMR spectroscopy of large non-deuterated proteins enabled by deep neural networks
Methyl-TROSY nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for characterising large biomolecules in solution. However, preparing samples for these experiments is demanding and entails deuteration, limiting its use. Here we demonstrate that NMR spectra recorded on protonated, uniformly ^(13)C labelled samples can be processed using deep neural networks to yield spectra that are of similar quality to typical deuterated methyl-TROSY spectra, potentially providing...
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06-14-2024 04:20 PM
Towards autonomous analysis of chemical exchange saturation transfer experiments using deep neural networks
Towards autonomous analysis of chemical exchange saturation transfer experiments using deep neural networks
Abstract
Macromolecules often exchange between functional states on timescales that can be accessed with NMR spectroscopy and many NMR tools have been developed to characterise the kinetics and thermodynamics of the exchange processes, as well as the structure of the conformers that are involved. However, analysis of the NMR data that report on exchanging macromolecules often hinges on complex least-squares fitting procedures as well as human...
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05-29-2022 03:31 AM
[NMR paper] DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra
DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra
The analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR analyses of complex biological molecular systems. Here, we introduce DEEP Picker, a deep neural network (DNN)-based approach for peak picking and spectral deconvolution which semi-automates the analysis of two-dimensional NMR spectra. DEEP Picker includes 8 hidden convolutional layers and was...
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09-04-2021 10:34 AM
Students bring 'fresh insights' to scientific research on gene expression, deep neural networks and more - Clark University News Hub
http://www.bionmr.com//t1.gstatic.com/images?q=tbn:ANd9GcTVd062HSNkufpFLOXoHxhOr1s0onXKhPyi91bbXm51srwsuet1eajYCvbuLO7yooXH_P0TNwUX
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Students bring 'fresh insights' to scientific research on gene expression, deep neural networks and more
Clark University News Hub
... biochemistry and molecular biology senior Pinky Htun '17 of Myanmar spent June and July isolating, purifying and studying proteins using state-of-the-art lab equipment, including a high-speed centrifuge and a nuclear magnetic resonance spectrometer.
Students...
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08-25-2016 05:42 AM
[NMR paper] Application of neural networks to automated assignment of NMR spectra of proteins.
Application of neural networks to automated assignment of NMR spectra of proteins.
Related Articles Application of neural networks to automated assignment of NMR spectra of proteins.
J Biomol NMR. 1994 Jan;4(1):35-46
Authors: Hare BJ, Prestegard JH
Simulated neural networks are described which aid the assignment of protein NMR spectra. A network trained to recognize amino acid type from TOCSY data was trained on 148 assigned spin systems from E. coli acyl carrier proteins (ACPs) and tested on spin systems from spinach ACP, which has a 37%...
Deep Neural Networks for Methyl NMR Spectroscopy of Large Proteins - MSN
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