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Multiclass classification of sarcomas using pathway based feature selection method.
- Source :
-
Journal of Theoretical Biology . Dec2014, Vol. 362, p3-8. 6p. - Publication Year :
- 2014
-
Abstract
- Feature selection is an important research topic in bioinformatics, to date a large number of methods have been developed. Recently several pathway based feature selection protocols, such as the condition-responsive genes method, have been proposed for better classification performance. However, these conventional pathway based methods may lead to the selection of relevant but redundant genes in a given pathway while missing the other useful genes. Also these methods were limited to binary classification, while in many clinical problems a multiclass protocol is preferred such as the classification of sarcomas. Here, we propose a new pathway based feature selection method named R edundancy R emovable P athway based feature selection method (RRP) for the binary and multiclass classification problems. Three classifiers were implemented to compare the performance and gene functions of gene-based, conventional pathway based, and our RRP method. The validation results suggest that the RRP method is a feasible and robust feature selection method for multi-class prediction problems. [ABSTRACT FROM AUTHOR]
- Subjects :
- *SARCOMA
*FEATURE selection
*NOSOLOGY
*GENES
*BIOINFORMATICS
Subjects
Details
- Language :
- English
- ISSN :
- 00225193
- Volume :
- 362
- Database :
- Academic Search Index
- Journal :
- Journal of Theoretical Biology
- Publication Type :
- Academic Journal
- Accession number :
- 99513814
- Full Text :
- https://doi.org/10.1016/j.jtbi.2014.06.038