Mining microarray data to predict the histological grade of a breast cancer.
J Biomed Inform
; 44 Suppl 1: S12-S16, 2011 Dec.
Article
em En
| MEDLINE
| ID: mdl-21397039
ABSTRACT
BACKGROUND:
The aim of this study was to develop an original method to extract sets of relevant molecular biomarkers (gene sequences) that can be used for class prediction and can be included as prognostic and predictive tools. MATERIALS ANDMETHODS:
The method is based on sequential patterns used as features for class prediction. We applied it to classify breast cancer tumors according to their histological grade.RESULTS:
We obtained very good recall and precision for grades 1 and 3 tumors, but, like other authors, our results were less satisfactory for grade 2 tumors.CONCLUSIONS:
We demonstrated the interest of sequential patterns for class prediction of microarrays and we now have the material to use them for prognostic and predictive applications.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Mama
/
Análise de Sequência com Séries de Oligonucleotídeos
/
Mineração de Dados
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Female
/
Humans
Idioma:
En
Ano de publicação:
2011
Tipo de documento:
Article