Selection of informative clusters from hierarchical cluster tree with gene classes
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Summary
This article presents a simple method for searching for clusters with the strongest enrichment of gene classes from a cluster tree and indicates that the clusters found could not have been obtained by simply cutting the cluster tree.
- Type
- article
- Published
- 2004-03-25
- Cited by
- 47
- References
- 12
- Access
- Open access
- OpenAlex
- https://openalex.org/W1788898868
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:268088031
Keywords
Hierarchical clustering, Cluster analysis, Computer science, Tree (set theory), Set (abstract data type)
References
- Computational and Statistical Approaches to Genomics
- Antipsychotic drug treatment induces differential gene expression in the rat cortex
- Large-scale prediction of Saccharomyces cerevisiae gene function using overlapping transcriptional clusters
- Analysis and visualization of gene expression data using Self-Organizing Maps
- Genome-wide discovery of transcriptional modules from DNA sequence and gene expression
- Functional discovery via a compendium of expression profiles.
- Saccharomyces Genome Database (SGD) provides biochemical and structural information for budding yeast proteins
- Cluster analysis and display of genome-wide expression patterns.
- Judging the quality of gene expression-based clustering methods using gene annotation.
- Discriminative Clustering: Optimal Contingency Tables by Learning Metrics
- Exploratory Clustering of Gene Expression Profiles of Mutated Yeast Strains
Cited by
- Algorithms to Explore the Structure and Evolution of Biological Networks
- Transcriptional memory emerges from cooperative histone modifications
- Estimation of identification methods of gene clusters using GO term annotations from a hierarchical cluster tree
- Computational analysis of gene expression data
- Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes
- Exploring genomic medicine using integrative biology
- Visual data mining in intrinsic hierarchical complex biodata
- Sequential and concerted gene expression changes in a chronic in vitro model of parkinsonism.
- Interspliced transcription chimeras: Neglected pathological mechanism infiltrating gene accession queries?
- An improved localization algorithm with wireless heartbeat monitoring system for patient safety in psychiatric wards
- DNA microarray study on gene expression profiles in co-cultured endothelial and smooth muscle cells in response to 4- and 24-h shear stress
- Age and sex differences in brain gene expression in neonatal rats.
- Techniques for clustering gene expression data
- Improving clustering with metabolic pathway data
- Using expression information to discover new drug and vaccine targets in the malaria parasite Plasmodium falciparum.
- Data Mining Over Biological Datasets: An Integrated Approach Based on Computational Intelligence
- Revised Phylogeny and Novel Horizontally Acquired Virulence Determinants of the Model Soft Rot Phytopathogen Pectobacterium wasabiae SCC3193
- Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
- Finding Biologically Accurate Clusterings in Hierarchical Tree Decompositions Using the Variation of Information
- Theme discovery from gene lists for identification and viewing of multiple functional groups
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