基于代自适应曲线拟合的质谱学的新型精确峰值提取算法
Fulong Deng1, Xingliang He1, Hanlu Yue2
1School of Mechanical Engineering, Sichuan University, Chengdu 610064, PR China.
Journal of the American Society for Mass Spectrometry
|October 1, 2024
概括
一个新的代自适应曲线拟合算法有效地提取质谱中的重叠峰值. 这种方法提高了复杂光谱的精度,有助于定性和定量分析.
科学领域:
- 分析化学 分析化学
- 频谱学是一种光谱学.
背景情况:
- 在质谱学中,峰值识别具有挑战性,尤其是在重叠信号的情况下.
- 现有的方法,如连续波形变换,具有复杂重叠的局限性.
研究的目的:
- 开发一种新的算法,以精确地从重叠区域中提取质谱峰值.
- 为了解决当前处理复杂和严重峰值重叠的方法的局限性.
主要方法:
- 提出了一种用于质谱的代自适应曲线拟合算法.
- 使用窗口搜索初始峰值参数和余数以进行代改进.
- 将该方法应用于模拟数据,公共数据集和来自不同仪器的真实光谱.
主要成果:
- 成功地从重叠区域中提取了所有峰值,即使重叠严重和多个峰值.
- 证明了对噪声干扰的稳定性和对高动态范围数据的潜力.
- 在现实世界的质谱数据中准确识别重叠的峰值.
结论:
- 代自适应曲线拟合方法在质谱学中为重叠的峰值提取提供了卓越的性能.
- 这种技术显著提高了定性和定量分析的准确性.
- 该算法显示,它有望在各种质谱仪器和复杂样品中广泛应用.
关键词:
曲线适合的 曲线适合的质谱测量质谱测量质谱测量质谱测量质量测量质谱测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量覆盖的峰值重叠在一起.分析频谱的分析.更多相关视频
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