Title :

Efficient denoising algorithms for large experimental datasets and their applications in Fourier transform ion cyclotron resonance mass spectrometry

Author(s) :

Chiron, Lionel [Auteur]
Institut de génétique et biologie moléculaire et cellulaire [IGBMC]
van Agthoven, Maria [Auteur]
Miniaturisation pour la Synthèse, l’Analyse et la Protéomique - UAR 3290 [MSAP]
Kieffer, Bruno [Auteur]
Institut de génétique et biologie moléculaire et cellulaire [IGBMC]
Rolando, Christian [Auteur]
Miniaturisation pour la Synthèse, l’Analyse et la Protéomique - UAR 3290 [MSAP]
Delsuc, Marc-André [Auteur]
Institut de génétique et biologie moléculaire et cellulaire [IGBMC]

Journal title :

Proceedings of the National Academy of Sciences of the United States of America

Pages :

1385-1390

Publisher :

National Academy of Sciences

Publication date :

2014-01-03

ISSN :

0027-8424

HAL domain(s) :

Sciences du Vivant [q-bio]/Biochimie, Biologie Moléculaire/Génomique, Transcriptomique et Protéomique [q-bio.GN]

English abstract : [en]

Significance Every measurement is corrupted due to random fluctuations in the sample and the apparatus. Current efficient denoising algorithms require large matrix analysis, and become untractable even for moderately large ...
Show more >Significance Every measurement is corrupted due to random fluctuations in the sample and the apparatus. Current efficient denoising algorithms require large matrix analysis, and become untractable even for moderately large datasets. Any series can be considered as an operator that modifies any input vector. By applying this operator on a series of random vectors and thus reducing the dimension of the data, it is possible, using simple algebra, to reduce noise in a robust manner. Furthermore, the structure of the underlying matrices allows a very fast and memory-efficient implementation. Counterintuitively, randomness is used here to reduce noise. This procedure, called urQRd (uncoiled random QR denoising), allows denoising to be applied to data of virtually unlimited size.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Miniaturisation pour la Synthèse, l'Analyse et la Protéomique (MSAP) - USR 3290

Source :

Harvested from HAL

Submission date :

2025-03-20T05:43:26Z