mokapot: Fast and Flexible Semisupervised Learning for Peptide Detection.
J Proteome Res
; 20(4): 1966-1971, 2021 04 02.
Article
en En
| MEDLINE
| ID: mdl-33596079
ABSTRACT
Proteomics studies rely on the accurate assignment of peptides to the acquired tandem mass spectra-a task where machine learning algorithms have proven invaluable. We describe mokapot, which provides a flexible semisupervised learning algorithm that allows for highly customized analyses. We demonstrate some of the unique features of mokapot by improving the detection of RNA-cross-linked peptides from an analysis of RNA-binding proteins and increasing the consistency of peptide detection in a single-cell proteomics study.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Péptidos
/
Proteómica
Tipo de estudio:
Diagnostic_studies
Idioma:
En
Revista:
J Proteome Res
Asunto de la revista:
BIOQUIMICA
Año:
2021
Tipo del documento:
Article
País de afiliación:
Estados Unidos