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Discovering Coherent Biclusters from Gene Expression Data Using Zero-Suppressed Binary Decision Diagrams

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Kernelized Infomax Clustering

We propose a simple information-theoretic clustering approach based on maximizing the mutual information

I(\sfx,y)

between the unknown cluster labels

y

and the training patterns

\sfx

with respect to parameters of specifically constrained encoding dis ...

IDIAP2005

Discovering Coherent Biclusters from Gene Expression Data Using Zero-Suppressed Binary Decision Diagrams

Graph Chatbot

Chat with Graph Search

A model-based optimization framework for the inference of regulatory interactions using time-course DNA microarray expression data

Learning Cluster Type and Dissimilarity Metric for Each Cluster Using a Set of Possible Cluster Types

Bioimaging and Functional Genomics

Computational Identification of MicroRNAs and Their Targets

Exploiting Binary Abstractions in Deciphering Gene Interactions

Finding Co-Clusters of Genes and Clinical Parameters

Kernelized Infomax Clustering

Microarray analysis of VEGF-C responsive genes in human lymphatic endothelial cells

Making Retrieval Faster Through Document Clustering

Classification of human astrocytic gliomas on the basis of gene expression: a correlated group of genes with angiogenic activity emerges as a strong predictor of subtypes

Bioimaging and Functional Genomics

Learning Cluster Type and Dissimilarity Metric for Each Cluster Using a Set of Possible Cluster Types

Classification of human astrocytic gliomas on the basis of gene expression: a correlated group of genes with angiogenic activity emerges as a strong predictor of subtypes

Kernelized Infomax Clustering

Finding Co-Clusters of Genes and Clinical Parameters

Microarray analysis of VEGF-C responsive genes in human lymphatic endothelial cells

Exploiting Binary Abstractions in Deciphering Gene Interactions

A model-based optimization framework for the inference of regulatory interactions using time-course DNA microarray expression data

Computational Identification of MicroRNAs and Their Targets

Making Retrieval Faster Through Document Clustering