| Title |
Fast multi-dimensional NMR acquisition and processing using the sparse FFT
|
|---|---|
| Published in |
Journal of Biomolecular NMR, June 2015
|
| DOI | 10.1007/s10858-015-9952-5 |
| Pubmed ID | |
| Authors |
Haitham Hassanieh, Maxim Mayzel, Lixin Shi, Dina Katabi, Vladislav Yu Orekhov |
| Abstract |
Increasing the dimensionality of NMR experiments strongly enhances the spectral resolution and provides invaluable direct information about atomic interactions. However, the price tag is high: long measurement times and heavy requirements on the computation power and data storage. We introduce sparse fast Fourier transform as a new method of NMR signal collection and processing, which is capable of reconstructing high quality spectra of large size and dimensionality with short measurement times, faster computations than the fast Fourier transform, and minimal storage for processing and handling of sparse spectra. The new algorithm is described and demonstrated for a 4D BEST-HNCOCA spectrum. |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 5% |
| Unknown | 35 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 30% |
| Student > Ph. D. Student | 9 | 24% |
| Other | 4 | 11% |
| Professor | 3 | 8% |
| Student > Master | 3 | 8% |
| Other | 3 | 8% |
| Unknown | 4 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 10 | 27% |
| Biochemistry, Genetics and Molecular Biology | 8 | 22% |
| Agricultural and Biological Sciences | 6 | 16% |
| Engineering | 4 | 11% |
| Physics and Astronomy | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 7 | 19% |
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 11 May 2017.
All research outputs
#7,552,525
of 23,039,416 outputs
Outputs from Journal of Biomolecular NMR
#132
of 616 outputs
Outputs of similar age
#89,485
of 263,384 outputs
Outputs of similar age from Journal of Biomolecular NMR
#2
of 14 outputs
Altmetric has tracked 23,039,416 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 616 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 48th percentile – i.e., 48% 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 263,384 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.