scholarly journals Analytic Properties of Statistical Total Correlation Spectroscopy Based Information Recovery in1H NMR Metabolic Data Sets

2009 ◽  
Vol 81 (6) ◽  
pp. 2075-2084 ◽  
Author(s):  
Alexessander Couto Alves ◽  
Mattias Rantalainen ◽  
Elaine Holmes ◽  
Jeremy K. Nicholson ◽  
Timothy M. D. Ebbels
Keyword(s):  
Correlation Spectroscopy ◽  
Data Sets ◽  
Information Recovery ◽  
Total Correlation ◽  
Metabolic Data

Data-Driven Approach for Metabolite Relationship Recovery in Biological1H NMR Data Sets Using Iterative Statistical Total Correlation Spectroscopy

2011 ◽  
Vol 83 (6) ◽  
pp. 2075-2082 ◽  
Author(s):  
Caroline J. Sands ◽  
Muireann Coen ◽  
Timothy M. D. Ebbels ◽  
Elaine Holmes ◽  
John C. Lindon ◽  
...  
Keyword(s):  
Correlation Spectroscopy ◽  
Data Driven ◽  
Data Sets ◽  
Nmr Data ◽  
Total Correlation ◽  
Data Driven Approach

Statistical Total Correlation Spectroscopy Editing of1H NMR Spectra of Biofluids: Application to Drug Metabolite Profile Identification and Enhanced Information Recovery

2009 ◽  
Vol 81 (15) ◽  
pp. 6458-6466 ◽  
Author(s):  
Caroline J. Sands ◽  
Muireann Coen ◽  
Anthony D. Maher ◽  
Timothy M. D. Ebbels ◽  
Elaine Holmes ◽  
...  
Keyword(s):  
Nmr Spectra ◽  
Metabolite Profile ◽  
Correlation Spectroscopy ◽  
Information Recovery ◽  
Total Correlation ◽  
Drug Metabolite

Dynamic Biochemical Information Recovery in Spontaneous Human Seminal Fluid Reactions via1H NMR Kinetic Statistical Total Correlation Spectroscopy

2009 ◽  
Vol 81 (1) ◽  
pp. 288-295 ◽  
Author(s):  
Anthony D. Maher ◽  
Olivier Cloarec ◽  
Prasad Patki ◽  
Michael Craggs ◽  
Elaine Holmes ◽  
...  
Keyword(s):  
Seminal Fluid ◽  
Correlation Spectroscopy ◽  
Information Recovery ◽  
Total Correlation

Statistical Total Correlation Spectroscopy:  An Exploratory Approach for Latent Biomarker Identification from Metabolic1H NMR Data Sets

2005 ◽  
Vol 77 (5) ◽  
pp. 1282-1289 ◽  
Author(s):  
Olivier Cloarec ◽  
Marc-Emmanuel Dumas ◽  
Andrew Craig ◽  
Richard H. Barton ◽  
Johan Trygg ◽  
...  
Keyword(s):  
Correlation Spectroscopy ◽  
Data Sets ◽  
Biomarker Identification ◽  
Nmr Data ◽  
Total Correlation ◽  
Exploratory Approach

Statistical Total Correlation Spectroscopy Scaling for Enhancement of Metabolic Information Recovery in Biological NMR Spectra

2011 ◽  
Vol 84 (2) ◽  
pp. 1083-1091 ◽  
Author(s):  
Anthony D. Maher ◽  
Judith M. Fonville ◽  
Muireann Coen ◽  
John C. Lindon ◽  
Caroline D. Rae ◽  
...  
Keyword(s):  
Nmr Spectra ◽  
Correlation Spectroscopy ◽  
Information Recovery ◽  
Total Correlation ◽  
Metabolic Information

Sequential assignment of NMR spectra of peptides at natural isotopic abundance with Zero and Ultra-Low Field-TOCSY

2021 ◽  
Author(s):  
Alexey S. Kiryutin ◽  
Ivan V. Zhukov ◽  
Fabien Ferrage ◽  
G Bodenhausen ◽  
Alexandra V. Yurkovskaya ◽  
...  
Keyword(s):  
High Field ◽  
Nmr Spectra ◽  
Correlation Spectroscopy ◽  
Sequential Assignment ◽  
Isotopic Abundance ◽  
Natural Isotopic Abundance ◽  
Low Field ◽  
Total Correlation ◽  
High Resolution Nmr ◽  
Novel Method

A novel method dubbed ZULF-TOCSY results from the combination of Zero and Ultra-Low Field (ZULF) with high-field, high-resolution NMR, leading to a generalization of the concept of total correlation spectroscopy...

scholarly journals Total Correlation Spectroscopy across All NMR-Active Nuclei by Mixing at Zero Field

2020 ◽  
Vol 11 (17) ◽  
pp. 7291-7296
Author(s):  
Ivan V. Zhukov ◽  
Alexey S. Kiryutin ◽  
Fabien Ferrage ◽  
Gerd Buntkowsky ◽  
Alexandra V. Yurkovskaya ◽  
...  
Keyword(s):  
Correlation Spectroscopy ◽  
Zero Field ◽  
Total Correlation

Fractional dynamics of allometry

2012 ◽  
Vol 15 (1) ◽  
Author(s):  
Bruce West ◽  
Damien West
Keyword(s):  
Fractal Geometry ◽  
Empirical Distribution ◽  
Linear Regression Analysis ◽  
The Other ◽  
Fractional Dynamics ◽  
Data Sets ◽  
Fractal Statistics ◽  
Metabolic Data ◽  
Detailed Application ◽  
Dynamic Variables

AbstractAllometry relations (ARs) in physiology are nearly two hundred years old. In general if X ij is a measure of the size of the i th member of a complex host network from species j and Y ij is a property of a complex subnetwork embedded within the host network an intraspecies AR exists between the two when Y ij = aX ijb. We emphasize that the reductionist models of AR interpret X ij and Y ij as dynamic variables, albeit the ARs themselves are explicitly time independent. On the other hand, the phenomenological models of AR are based on the statistical analysis of data and interpret 〈X i〉 and 〈Y i〉 as averages over an ensemble of individuals to yields the interspecies AR 〈Y i〉 = a〈X i〉b. Modern explanations of AR begin with the application of fractal geometry and fractal statistics to scaling phenomena. The detailed application of fractal geometry to the explanation of intraspecies ARs is a little over a decade old and although well received it has not been universally accepted. An alternate perspective is given by the interspecies AR based on linear regression analysis of fluctuating data sets. We emphasize that the intraspecies and interspecies ARs are not the same and show that the interspecies AR can only be derived from the intraspecies one for a narrow distribution of fluctuations. This condition is not satisfied by metabolic data as is shown separately for aviary and mammal data sets. The empirical distribution of metabolic allometry coefficients is shown herein to be Pareto in form. A number of reductionist arguments conclude that the allometry exponent is universal, however herein we derive a deterministic relation between the allometry exponent and the allometry coefficient using the fractional calculus. The co-variation relation violates the universality assumption. We conclude that the interspecies physiologic AR is entailed by the scaling behavior of the probability density, which is derived using the fractional probability calculus.

Moving Window Two-Dimensional Correlation Spectroscopy and Determination of Signal-To-Noise Threshold in Correlation Spectra

2003 ◽  
Vol 57 (8) ◽  
pp. 996-1006 ◽  
Author(s):  
Slobodan Šašić ◽  
Yukihiro Ozaki
Keyword(s):  
Large Data ◽  
Correlation Spectroscopy ◽  
Data Matrix ◽  
Data Sets ◽  
Complex Data ◽  
Moving Window ◽  
Two Dimensional ◽  
Complex Data Sets ◽  
Coexisting Species ◽  
Definition Of

In this paper we report two new developments in two-dimensional (2D) correlation spectroscopy; one is the combination of the moving window concept with 2D spectroscopy to facilitate the analysis of complex data sets, and the other is the definition of the noise level in synchronous/asynchronous maps. A graphical criterion for the latter is also proposed. The combination of the moving window concept with correlation spectra allows one to split a large data matrix into smaller and simpler subsets and to analyze them instead of computing overall correlation. A three-component system that mimics a consecutive chemical reaction is used as a model for the illustration of the two ideas. Both types of correlation matrices, variable–variable and sample–sample, are analyzed, and a very good agreement between the two is met. The proposed innovations enable one to comprehend the complexity of the data to be analyzed by 2D spectroscopy and thus to avoid the risks of over-interpretation, liable to occur whenever improper caution about the number of coexisting species in the system is taken.

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