To Enhance The Quality Of Fourier Transform Mass Spectrometry Data Based On The Filter Diagonalization Method

Mass spectrometry has been throughout the various disciplines, while the application for life sciences provides a broad platform for the development of mass spectrometry. The quality control of mass spectrometry data is a bottleneck for restricting the analysis efficiency. It has been a hot topic to improve the quality of mass spectral data that has a direct impact on the outcome of the research. It not only brings difficult to the research, but also calls in question for the result of the research.Therefore, it is important for doing the research.Fourier transform mass spectrometry(FTMS) is capable of achieving very high resolution, which is widely used in molecular biological research. Data processing method, especially these at the signal level, is crucial for improving the quality of the data. In the paper, we study an new algorithm which was called filter diagonalization method(FDM) in order to exploit the potential to extract the original data in the front of Fourier spectrometer. It is the latest try for extracting the original data in the front of Fourier spectrometer. For example, the mass to charge ratio.Through the simulation data and experimental mass spectrometry data analysis shows, compared to Fast Fourier Transform method(FFT), FDM improved the resolution of the mass spectra by a factor of one order and reduced the measured signal error effectively in experimental mass spectrometry data. Meanwhile, this work also investigated the parameter optimization problem that could be a reference for the application of FDM.