multimrfit:一个软件拟合1D和伪2d核磁共振光谱。

IF 5.4
Pierre Millard, Loïc Le Grégam, Svetlana Dubiley, Valeria Gabrielli, Thomas Gosselin-Monplaisir, Guy Lippens, Cyril Charlier
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引用次数: 0

摘要

动机:核磁共振(NMR)广泛用于代谢系统的定量分析。准确提取核磁共振信号参数,如化学位移,强度,耦合常数和线宽,是必不可少的信息,获取结构,浓度和代谢物的同位素组成。结果:我们提出了一个开源软件,用于一维核磁共振光谱的高通量分析,无论是单独获得还是作为伪二维实验。MultiNMRFit通过使用内置或用户定义的信号模型拟合实验光谱来提取信号参数(例如强度,面积,化学位移和耦合常数),这些模型考虑了多样性,提供了高度的灵活性以及鲁棒性和可重复性的结果。该软件既可以作为Python库访问,也可以通过图形用户界面访问,使没有计算专业知识的最终用户能够直观地使用。我们在代谢组学和同位素标记研究中收集的1H、13C和31P核磁共振数据集上展示了multinmnmrfit的稳健性和灵活性。可用性:MultiNMRFit在Python 3中实现,并在Unix、Windows和MacOS平台上进行了测试。源代码和文档在GPL3许可下分别在https://github.com/NMRTeamTBI/MultiNMRFit/和https://multinmrfit.readthedocs.io免费发布。补充信息:补充数据可在生物信息学在线获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

MultiNMRFit: a software to fit 1D and pseudo-2D NMR spectra.

MultiNMRFit: a software to fit 1D and pseudo-2D NMR spectra.

MultiNMRFit: a software to fit 1D and pseudo-2D NMR spectra.

MultiNMRFit: a software to fit 1D and pseudo-2D NMR spectra.

Motivation: Nuclear Magnetic Resonance (NMR) is widely used for quantitative analysis of metabolic systems. Accurate extraction of NMR signal parameters-such as chemical shift, intensity, coupling constants, and linewidth-is essential for obtaining information on the structure, concentration, and isotopic composition of metabolites.

Results: We present MultiNMRFit, an open-source software designed for high-throughput analysis of 1D NMR spectra, whether acquired individually or as pseudo-2D experiments. MultiNMRFit extracts signal parameters (e.g. intensity, area, chemical shift, and coupling constants) by fitting the experimental spectra using built-in or user-defined signal models that account for multiplicity, providing high flexibility along with robust and reproducible results. The software is accessible both as a Python library and via a graphical user interface, enabling intuitive use by end-users without computational expertise. We demonstrate the robustness and flexibility of MultiNMRFit on 1H, 13C, and 31P NMR datasets collected in metabolomics and isotope labeling studies.

Availability and implementation: MultiNMRFit is implemented in Python 3 and was tested on Unix, Windows, and MacOS platforms. The source code and the documentation are freely distributed under GPL3 license at https://github.com/NMRTeamTBI/MultiNMRFit/ and https://multinmrfit.readthedocs.io, respectively.

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