Abstract
We introduce NMR-Onion, an open-source, computationally efficient algorithm based on Python and PyTorch, designed to facilitate the automatic deconvolution of 1D NMR spectra. NMR-Onion features two innovative time-domain models capable of handling asymmetric non-Lorentzian line shapes. Its core components for resolution-enhanced peak detection and digital filtering of user-specified key regions ensure precise peak prediction and efficient computation. The NMR-Onion framework includes three built-in statistical models, with automatic selection via the BIC criterion. Additionally, NMR-Onion assesses the repeatability of results by evaluating post-modeling uncertainty. Using the NMR-Onion algorithm helps to minimize excessive peak detection.
Original language | English |
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Article number | e36998 |
Journal | Heliyon |
Volume | 10 |
Issue number | 17 |
Number of pages | 19 |
ISSN | 2405-8440 |
DOIs | |
Publication status | Published - 2024 |
Keywords
- Statistical evidence
- Time domain models
- Open source
- Deconvolution
- High sensitivity
- Extensive overlaps
- Computationally efficiency