Deep learning dreams up new protein structures: A neural network trained exclusively to predict protein shapes can also generate new ones. - Science Daily
Deep learning dreams up new protein structures: A neural network trained exclusively to predict protein shapes can also generate new ones. - Science Daily
[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...
[NMR paper] FID-Net: A versatile deep neural network architecture for NMR spectral reconstruction and virtual decoupling
FID-Net: A versatile deep neural network architecture for NMR spectral reconstruction and virtual decoupling
In recent years, the transformative potential of deep neural networks (DNNs) for analysing and interpreting NMR data has clearly been recognised. However, most applications of DNNs in NMR to date either struggle to outperform existing methodologies or are limited in scope to a narrow range of data that closely resemble the data that the network was trained on. These limitations have prevented a widescale uptake of DNNs in NMR. Addressing this, we introduce FID-Net, a deep neural...
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04-20-2021 12:46 PM
FID-Net: A versatile deep neural network architecture for NMR spectral reconstruction and virtual decoupling
FID-Net: A versatile deep neural network architecture for NMR spectral reconstruction and virtual decoupling
Abstract
In recent years, the transformative potential of deep neural networks (DNNs) for analysing and interpreting NMR data has clearly been recognised. However, most applications of DNNs in NMR to date either struggle to outperform existing methodologies or are limited in scope to a narrow range of data that closely resemble the data that the network was trained on. These limitations have prevented a widescale uptake of DNNs in NMR....
[ASAP] The Protein Biochemistry of the Postsynaptic Density in Glutamatergic Synapses Mediates Learning in Neural Networks
The Protein Biochemistry of the Postsynaptic Density in Glutamatergic Synapses Mediates Learning in Neural Networks
https://pubs.acs.org/appl/literatum/publisher/achs/journals/content/bichaw/0/bichaw.ahead-of-print/acs.biochem.8b00496/20180702/images/medium/bi-2018-00496z_0004.gif
Biochemistry
DOI: 10.1021/acs.biochem.8b00496
http://feeds.feedburner.com/~ff/acs/bichaw?d=yIl2AUoC8zA
http://feeds.feedburner.com/~r/acs/bichaw/~4/P7CcZMyUuio
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07-06-2018 09:40 AM
New Technology Provides a Deep View Into Protein Structures - Science Daily (press release)
New Technology Provides a Deep View Into Protein Structures - Science Daily (press release)
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New Technology Provides a Deep View Into Protein Structures
Science Daily (press release)
The stability of a thermodynamic system, such as a protein, can be analyzed by subjecting it to variations in pressure and temperature. Using high resolution NMR methods and a newly developed pressure cell Nisius and Grzesiek have precisely analyzed ...
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