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- W32017579 abstract "A new peak picking algorithm for the analysis of mass spectrometric (MS) data is presented, which is independent of the underlying machine or ion- ization method and is able to resolve highly convoluted and asymmetric signals. The method uses the multiscale nature of spectrometric data by first detectin g the mass peaks in the wavelet-transformed signal. Then, a given asymmetric peak function is fitted to the raw data. In an optional third stage, the resulting fit can be further improved using techniques from nonlinear optimization. In contrast to currently established techniques (e.g. SNAP, Apex) our algorithm is able to separate overlapping peaks of multiply charged peptides in ESI-MS data of low resolution. Its improved accuracy with respect to peak positions makes it a valu- able preprocessing method for MS-based identification and quantification exper- iments. The method has been validated on a number of different annotated test cases, where it compares favorably in both runtime and accuracy with currently established techniques. An implementation of the algorithm is freely available in our open source framework OpenMS." @default.
- W32017579 created "2016-06-24" @default.
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- W32017579 date "2005-01-01" @default.
- W32017579 modified "2023-09-26" @default.
- W32017579 title "High-accuracy peak picking of proteomics data" @default.
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