scholarly journals Metal Binding in Proteins: Machine Learning Complements X-Ray Absorption Spectroscopy

2012 ◽  
pp. 854-857 ◽  
Author(s):  
Marco Lippi ◽  
Andrea Passerini ◽  
Marco Punta ◽  
Paolo Frasconi
Keyword(s):  
Machine Learning ◽  
Absorption Spectroscopy ◽  
Metal Binding ◽  
X Ray ◽  
X Ray Absorption

The Nickel Site ofBacilluspasteuriiUreE, a Urease Metallo-Chaperone, As Revealed by Metal-Binding Studies and X-ray Absorption Spectroscopy†

Biochemistry ◽  
2006 ◽  
Vol 45 (20) ◽  
pp. 6495-6509 ◽  
Author(s):  
Massimiliano Stola ◽  
Francesco Musiani ◽  
Stefano Mangani ◽  
Paola Turano ◽  
Niyaz Safarov ◽  
...  
Keyword(s):  
Absorption Spectroscopy ◽  
Metal Binding ◽  
Binding Studies ◽  
X Ray ◽  
X Ray Absorption

Probing Active Sites in CuxPdy Cluster Catalysts by Machine-Learning-Assisted X-ray Absorption Spectroscopy

2021 ◽  
Author(s):  
Yang Liu ◽  
Avik Halder ◽  
Soenke Seifert ◽  
Nicholas Marcella ◽  
Stefan Vajda ◽  
...  
Keyword(s):  
Machine Learning ◽  
Absorption Spectroscopy ◽  
Active Sites ◽  
X Ray ◽  
X Ray Absorption

X-ray absorption spectroscopy combined with machine learning for diagnosis of schistosomiasis cirrhosis

2020 ◽  
Vol 60 ◽  
pp. 101944
Author(s):  
Zheng Fang ◽  
Weifeng Hu ◽  
Mengyi Wang ◽  
Renbin Wang ◽  
Shuo Zhong ◽  
...  
Keyword(s):  
Machine Learning ◽  
Absorption Spectroscopy ◽  
X Ray ◽  
X Ray Absorption

scholarly journals Stellacyanin. Studies of the metal-binding site using x-ray absorption spectroscopy

1982 ◽  
Vol 38 (3) ◽  
pp. 277-285 ◽  
Author(s):  
J. Peisach ◽  
L. Powers ◽  
W.E. Blumberg ◽  
B. Chance
Keyword(s):  
Binding Site ◽  
Absorption Spectroscopy ◽  
Metal Binding ◽  
Metal Binding Site ◽  
X Ray ◽  
X Ray Absorption

Absorption of Hydrocarbons on Palladium Catalysts: From Simple Models Towards Machine Learning Analysis of X-ray Absorption Spectroscopy Data

2020 ◽  
Vol 63 (1-2) ◽  
pp. 58-65 ◽  
Author(s):  
Oleg A. Usoltsev ◽  
Aram L. Bugaev ◽  
Alexander A. Guda ◽  
Sergey A. Guda ◽  
Alexander V. Soldatov
Keyword(s):  
Machine Learning ◽  
Absorption Spectroscopy ◽  
Palladium Catalysts ◽  
Spectroscopy Data ◽  
X Ray ◽  
X Ray Absorption ◽  
Learning Analysis ◽  
Simple Models

Unsupervised machine learning for unbiased chemical classification in X-ray absorption spectroscopy and X-ray emission spectroscopy

2021 ◽  
Author(s):  
Samantha Tetef ◽  
Niranjan Govind ◽  
Gerald T. Seidler
Keyword(s):  
Machine Learning ◽  
Absorption Spectroscopy ◽  
Emission Spectroscopy ◽  
Emission Spectra ◽  
Relevant Information ◽  
Unsupervised Machine Learning ◽  
Edge Structure ◽  
X Ray ◽  
X Ray Absorption

We utilize unsupervised machine learning to extract chemically relevant information in X-ray absorption near-edge structure (XANES) and in valence-to-core X-ray emission spectra (VtC-XES) for classification of an ensemble of sulphorganic molecules.

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