GP-based MS/MS spectrum denoising
post-processor · Peak selection
GP-based MS/MS spectrum denoising: post-processor · Peak selection. Genetic programming classifiers that separate b/y-ion peaks from noise before identification, raising PEAKS de novo identification rates on noisy CID spectra.
Genetic programming classifiers that separate b/y-ion peaks from noise before identification, raising PEAKS de novo identification rates on noisy CID spectra.
| Kind | post-processor |
| Deep learning | no |
| Acquisition | DDA |
| Family | Peak selection |
Papers describing it (2)
- Preprocessing Tandem Mass Spectra Using Genetic Programming for Peptide Identification (2019, Journal of the American Society for Mass Spectrometry, peer-reviewed)
- A Decomposition Based Multi-objective Genetic Programming Algorithm for Classification of Highly Imbalanced Tandem Mass Spectrometry (2020, Lecture Notes in Computer Science, peer-reviewed)