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Application of independent component analysis to microarrays
We apply linear and nonlinear independent component analysis (ICA) to project microarray data into statistically independent components that correspond to putative biological processes, and to cluster genes according to over- or under-expression in each component. We test the statistical significanc...
| Autores principales: | , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2003
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC329130/ https://www.ncbi.nlm.nih.gov/pubmed/14611662 |