Background: Network Component Analysis (NCA) has shown its effectiveness in discovering regulators and inferring transcription factor activities (TFAs) when both microarray data a...
Chen Wang, Jianhua Xuan, Li Chen, Po Zhao, Yue Wan...
Background: Microarray experiments measure changes in the expression of thousands of genes. The resulting lists of genes with changes in expression are then searched for biologica...
A method of extracting, classifying and modelling non-rigid shapes from an image sequence is presented. Shapes are approximated by polygons where the number of sides is related to...
Background: Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. Finding an appropriate (dis)similarity measure is crit...
Kyungpil Kim, Shibo Zhang, Keni Jiang, Li Cai, In-...
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...