Cargando…
Fuzzy Logic for Elimination of Redundant Information of Microarray Data
Gene subset selection is essential for classification and analysis of microarray data. However, gene selection is known to be a very difficult task since gene expression data not only have high dimensionalities, but also contain redundant information and noises. To cope with these difficulties, this...
Autores principales: | Huerta, Edmundo Bonilla, Duval, Béatrice, Hao, Jin-Kao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2008
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5054105/ https://www.ncbi.nlm.nih.gov/pubmed/18973862 http://dx.doi.org/10.1016/S1672-0229(08)60021-2 |
Ejemplares similares
-
Robust Fuzzy Logic Stabilization with Disturbance Elimination
por: Danapalasingam, Kumeresan A.
Publicado: (2014) -
Method for the estimation of institutional quality indexes using fuzzy logic
por: Ribeiro, Vinícius Souza
Publicado: (2022) -
Using the fuzzy logic approach to extract the index of economic sanctions in the Islamic Republic of Iran
por: Iranmanesh, Saeed, et al.
Publicado: (2021) -
Correction of technical bias in clinical microarray data improves concordance with known biological information
por: Eklund, Aron C, et al.
Publicado: (2008) -
Fuzzy logic
por: Smets, P
Publicado: (1995)