Optimization and automation of quantitative NMR data extraction
| Autor: | Chen Peng, Stan Sýkora, Michael A. Bernstein, Carlos Cobas, Agustin Barba |
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| Rok vydání: | 2013 |
| Předmět: |
Analyte
Data processing Electronic Data Processing Magnetic Resonance Spectroscopy business.industry Chemistry Analytical chemistry Pattern recognition Sample (statistics) computer.software_genre Automation Expert system Analytical Chemistry Pharmaceutical Solutions Workflow Data extraction Deconvolution Artificial intelligence business computer Algorithms |
| Zdroj: | Analytical chemistry. 85(12) |
| ISSN: | 1520-6882 |
| Popis: | NMR is routinely used to quantitate chemical species. The necessary experimental procedures to acquire quantitative data are well-known, but relatively little attention has been applied to data processing and analysis. We describe here a robust expert system that can be used to automatically choose the best signals in a sample for overall concentration determination and determine analyte concentration using all accepted methods. The algorithm is based on the complete deconvolution of the spectrum which makes it tolerant of cases where signals are very close to one another and includes robust methods for the automatic classification of NMR resonances and molecule-to-spectrum multiplets assignments. With the functionality in place and optimized, it is then a relatively simple matter to apply the same workflow to data in a fully automatic way. The procedure is desirable for both its inherent performance and applicability to NMR data acquired for very large sample sets. |
| Databáze: | OpenAIRE |
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