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Mendeley readers
| Title |
IQMNMR: Open source software using time-domain NMR data for automated identification and quantification of metabolites in batches
|
|---|---|
| Published in |
BMC Bioinformatics, August 2011
|
| DOI | 10.1186/1471-2105-12-337 |
| Pubmed ID | |
| Authors |
Xu Song, Bo-Li Zhang, Hong-Min Liu, Bo-Yang Yu, Xiu-Mei Gao, Li-Yuan Kang |
| Abstract |
One of the most promising aspects of metabolomics is metabolic modeling and simulation. Central to such applications is automated high-throughput identification and quantification of metabolites. NMR spectroscopy is a reproducible, nondestructive, and nonselective method that has served as the foundation of metabolomics studies. However, the automated high-throughput identification and quantification of metabolites in NMR spectroscopy is limited by severe spectral overlap. Although numerous software programs have been developed for resolving overlapping resonances, as well as for identifying and quantifying metabolites, most of these programs are frequency-domain methods, considerably influenced by phase shifts and baseline distortions, and effective only in small-scale studies. Almost all these programs require multiple spectra for each application, and do not automatically identify and quantify metabolites in batches. |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 3 | 8% |
| Switzerland | 1 | 3% |
| Spain | 1 | 3% |
| Unknown | 35 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 38% |
| Student > Ph. D. Student | 7 | 18% |
| Student > Master | 5 | 13% |
| Professor > Associate Professor | 4 | 10% |
| Student > Doctoral Student | 2 | 5% |
| Other | 5 | 13% |
| Unknown | 2 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 14 | 35% |
| Engineering | 5 | 13% |
| Chemistry | 5 | 13% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Environmental Science | 2 | 5% |
| Other | 8 | 20% |
| Unknown | 3 | 8% |