a novel preprocessing method using hilbert huang transform for maldi-tof and seldi-tof mass spectrometry data一种新的预处理方法使用希尔伯特黄变换maldi-tof和seldi-tof质谱数据.pdfVIP
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a novel preprocessing method using hilbert huang transform for maldi-tof and seldi-tof mass spectrometry data一种新的预处理方法使用希尔伯特黄变换maldi-tof和seldi-tof质谱数据
A Novel Preprocessing Method Using Hilbert Huang
Transform for MALDI-TOF and SELDI-TOF Mass
Spectrometry Data
1,2 1 1,3,4 1 1,5
Li-Ching Wu *, Hsin-Hao Chen , Jorng-Tzong Horng , Chen Lin , Norden E. Huang , Yu-Che
Cheng6, Kuang-Fu Cheng7,8
1 Graduate Institute of System Biology and Bioinformatics, National Central University, Jhongli, Taiwan, 2 Research Center for Biotechnology and Biomedical Engineering,
National Central University, Jhongli, Taiwan, 3 Department of Computer Science and Information Engineering, National Central University, Jhongli, Taiwan, 4 Department
of Bioinformatics, Asia University, Wu-feng, Taiwan, 5 Research Center for Adaptive Data Analysis, National Central University, Jhongli, Taiwan, 6 Proteomics Laboratory,
Cathay Medical Research Institute, Cathay General Hospital, Xizhi, Taiwan, 7 Graduate Institute of Statistics, National Central University, Jhongli, Taiwan, 8 Graduate
Institute of Statistics, China Medical University, Taichung, Taiwan
Abstract
Motivation: Mass spectrometry is a high throughput, fast, and accurate method of protein analysis. Using the peaks
detected in spectra, we can compare a normal group with a disease group. However, the spectrum is complicated by scale
shifting and is also full of noise. Such shifting makes the spectra non-stationary and need to align before comparison.
Consequently, the preprocessing of the mass data plays an important role during the analysis process. Noises in mass
spectrometry data come in lots of different aspects and frequencies. A powerful data preprocessing method is needed for
removing large amount of noises in mass spectrometry data.
Results: Hilbert-Huang Transformation is
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