Independent Principal Component Analysis for biologically meaningful dimension reduction of large biological data sets
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1471-2105
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Independent Principal Component Analysis for biologically meaningful dimension reduction of large biological data sets ; volume:13 ; number:1 ; day:3 ; month:2 ; year:2012 ; pages:1-15 ; date:12.2012
BMC bioinformatics ; 13, Heft 1 (3.2.2012), 1-15, 12.2012
- Creator
-
Yao, Fangzhou
- Contributor
-
Coquery, Jeff
Lê Cao, Kim-Anh
SpringerLink (Online service)
- DOI
-
10.1186/1471-2105-13-24
- URN
-
urn:nbn:de:1111-2016021733066
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
- 15.08.2025, 7:29 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Yao, Fangzhou
- Coquery, Jeff
- Lê Cao, Kim-Anh
- SpringerLink (Online service)
Other Objects (12)
Biologically meaningful classification of protein sequences : a bioinformatic approach
Independent component analysis reveals new and biologically significant structures in micro array data
Principal component analysis
Principal component analysis
Biologically meaningful moonlight measures and their application in ecological research
Meaningful managerial action planning: The financial component
Nonlinear principal component analysis
Evaluation and optimization of biologically meaningful dimensionality reduction approaches for MRI data
A nonlinear principal component decomposition
Uncertainty-Aware Principal Component Analysis
Independent nonlinear component analysis
Error-Gated Hebbian Rule: A Local Learning Rule for Principal and Independent Component Analysis
Biologically meaningful classification of protein sequences : a bioinformatic approach
Independent component analysis reveals new and biologically significant structures in micro array data
Principal component analysis
Principal component analysis
Biologically meaningful moonlight measures and their application in ecological research
Meaningful managerial action planning: The financial component
Nonlinear principal component analysis
Evaluation and optimization of biologically meaningful dimensionality reduction approaches for MRI data
A nonlinear principal component decomposition
Uncertainty-Aware Principal Component Analysis
Independent nonlinear component analysis
Error-Gated Hebbian Rule: A Local Learning Rule for Principal and Independent Component Analysis
Biologically meaningful classification of protein sequences : a bioinformatic approach
Independent component analysis reveals new and biologically significant structures in micro array data
Principal component analysis
Principal component analysis
Biologically meaningful moonlight measures and their application in ecological research
Meaningful managerial action planning: The financial component
Nonlinear principal component analysis
Evaluation and optimization of biologically meaningful dimensionality reduction approaches for MRI data
A nonlinear principal component decomposition
Uncertainty-Aware Principal Component Analysis
Independent nonlinear component analysis