Feature selection and machine learning with mass spectrometry data.
Methods Mol Biol
; 593: 205-29, 2010.
Article
en En
| MEDLINE
| ID: mdl-19957152
ABSTRACT
Mass spectrometry has been used in biochemical research for a long time. However, its potential for discovering proteomic biomarkers using protein mass spectra has aroused tremendous interest in the last few years. In spite of its potential for biomarker discovery, it is recognized that the identification of meaningful proteomic features from mass spectra needs careful evaluation. Hence, extracting meaningful features and discriminating the samples based on these features are still open areas of research. Several research groups are actively involved in making the process as perfect as possible. In this chapter, we provide a review of major contributions toward feature selection and classification of proteomic mass spectra involving MALDI-TOF and SELDI-TOF technology.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Espectrometría de Masas
/
Inteligencia Artificial
Límite:
Humans
Idioma:
En
Revista:
Methods Mol Biol
Asunto de la revista:
BIOLOGIA MOLECULAR
Año:
2010
Tipo del documento:
Article
País de afiliación:
Estados Unidos