Literature DB >> 11681466

The use of wavelets for signal denoising in capillary electrophoresis.

C Perrin1, B Walczak, D L Massart.   

Abstract

The discrete wavelet transform was applied to denoise electropherograms in capillary electrophoresis (CE). The use of the Haar wavelet and translation invariant denoising were found to be very efficient for this purpose. An important improvement was obtained, as compared with Savitzky-Golay and Fourier, which are the most commonly used techniques for denoising in the instrumentation software packages. A better removal of the noise and, especially, a better preservation of the shapes of very sharp peaks was achieved. Removal of the baseline variations was also investigated.

Year:  2001        PMID: 11681466     DOI: 10.1021/ac010416a

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  5 in total

1.  Untargeted analysis of mass spectrometry data for elucidation of metabolites and function of enzymes.

Authors:  Raymundo Sanchez-Ponce; F Peter Guengerich
Journal:  Anal Chem       Date:  2007-04-05       Impact factor: 6.986

2.  Normalization in MALDI-TOF imaging datasets of proteins: practical considerations.

Authors:  Sören-Oliver Deininger; Dale S Cornett; Rainer Paape; Michael Becker; Charles Pineau; Sandra Rauser; Axel Walch; Eryk Wolski
Journal:  Anal Bioanal Chem       Date:  2011-04-12       Impact factor: 4.142

3.  The knowledge-integrated network biomarkers discovery for major adverse cardiac events.

Authors:  Guangxu Jin; Xiaobo Zhou; Honghui Wang; Hong Zhao; Kemi Cui; Xiang-Sun Zhang; Luonan Chen; Stanley L Hazen; King Li; Stephen T C Wong
Journal:  J Proteome Res       Date:  2008-07-30       Impact factor: 4.466

4.  Microfluidic chemical cytometry of peptide degradation in single drug-treated acute myeloid leukemia cells.

Authors:  Michelle L Kovarik; Pavak K Shah; Paul M Armistead; Nancy L Allbritton
Journal:  Anal Chem       Date:  2013-05-02       Impact factor: 6.986

5.  Enhanced Multiscale Principal Component Analysis for Improved Sensor Fault Detection and Isolation.

Authors:  Byanne Malluhi; Hazem Nounou; Mohamed Nounou
Journal:  Sensors (Basel)       Date:  2022-07-26       Impact factor: 3.847

  5 in total

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