↓ Skip to main content

NMR Spectral Quantitation by Principal Component Analysis III. A Generalized Procedure for Determination of Lineshape Variations

Overview of attention for article published in Journal of Magnetic Resonance, February 2002
Altmetric Badge

Mentioned by

patent
3 patents

Readers on

mendeley
49 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Article details
Title
NMR Spectral Quantitation by Principal Component Analysis III. A Generalized Procedure for Determination of Lineshape Variations
Published in
Journal of Magnetic Resonance, February 2002
DOI 10.1006/jmre.2001.2486
Pubmed ID
Authors
Abstract

We present a general procedure for automatic quantitation of a series of spectral peaks based on principal component analysis (PCA). PCA has been previously used for spectral quantitation of a single resonant peak of constant shape but variable amplitude. Here we extend this procedure to estimate all of the peak parameters: amplitude, position (frequency), phase and linewidth. The procedure consists of a series of iterative steps in which the estimates of position and phase from one stage of iteration are used to correct the spectra prior to the next stage. The process is convergent to a stable result, typically in less than 5 iterations. If desired, remaining linewidth variations can then be corrected. Correction of (typically) unwanted variations of these types is important not only for direct peak quantitation, but also as a preprocessing step for spectral data prior to application of pattern recognition/classification techniques. The procedure is demonstrated on simulated data and on a set of 992 (31)P NMR in vivo spectra taken from a kinetic study of rat muscle energetics. The proposed procedure is robust, makes very limited assumptions about the lineshape, and performs well with data of low signal-to-noise ratio.

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
Russia 1 2%
Mexico 1 2%
United Kingdom 1 2%
Germany 1 2%
Switzerland 1 2%
Belgium 1 2%
Unknown 43 88%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 15 31%
Student > Ph. D. Student 10 20%
Professor 6 12%
Student > Bachelor 3 6%
Student > Master 3 6%
Other 7 14%
Unknown 5 10%
Readers by discipline
Readers by discipline Count As %
Chemistry 11 22%
Agricultural and Biological Sciences 8 16%
Physics and Astronomy 5 10%
Engineering 4 8%
Computer Science 3 6%
Other 5 10%
Unknown 13 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 February 2013.
All research outputs
#9,515,738
of 27,781,301 outputs
Outputs from Journal of Magnetic Resonance
#723
of 2,117 outputs
Outputs of similar age
#38,342
of 144,566 outputs
Outputs of similar age from Journal of Magnetic Resonance
#6
of 16 outputs
Altmetric has tracked 27,781,301 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,117 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 144,566 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.