ArticleBMC bioinformatics2009
R/BHC: fast Bayesian hierarchical clustering for microarray data.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Triclustering Model for Three-Dimensional Time-Series Gene Expression Data.International journal of molecular sciences · 2026Article
- Clustering of chemical profiles ofIndustrial crops and products · 2025Article
- VICatMix: variational Bayesian clustering and variable selection for discrete biomedical data.Bioinformatics advances · 2025Article
- Identification of MicroRNA Drug Targets for Alzheimer's and Diabetes Mellitus Using Network Medicine.Current Alzheimer research · 2025Article
- Bayesian cluster analysis.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023Review
- Understanding the nature of face processing in early autism: A prospective study.Journal of psychopathology and clinical science · 2022Article
- Transcriptome Analysis of Schwann Cells at Various Stages of Myelination Implicates Chromatin Regulator Sin3A in Control of Myelination Identity.Neuroscience bulletin · 2022Article
- New confinement index and new perspective for comparing countries - COVID-19.Computer methods and programs in biomedicine · 2021Article
- Revealing nuclear receptor hub modules from Basal-like breast cancer expression networks.PloS one · 2021Article
- Succession of physiological stages hallmarks the transcriptomic response of the fungusBiotechnology for biofuels · 2020Article
- Fast approximate inference for variable selection in Dirichlet process mixtures, with an application to pan-cancer proteomics.Statistical applications in genetics and molecular biology · 2019Article
- Relationship between the lipid composition of maternal plasma and infant plasma through breast milk.Metabolomics : Official journal of the Metabolomic Society · 2019Observational
- Fast hierarchical Bayesian analysis of population structure.Nucleic acids research · 2019Article
- Cluster analysis of replicated alternative polyadenylation data using canonical correlation analysis.BMC genomics · 2019Article
- Clustering gene expression time series data using an infinite Gaussian process mixture model.PLoS computational biology · 2018Article
- Genome wide analysis of protein production load in Trichoderma reesei.Biotechnology for biofuels · 2016Article
- A genetic framework for H2O2 induced cell death in Arabidopsis thaliana.BMC genomics · 2015Article
- A Bayesian Alternative to Mutual Information for the Hierarchical Clustering of Dependent Random Variables.PloS one · 2015Article
- Wigwams: identifying gene modules co-regulated across multiple biological conditions.Bioinformatics (Oxford, England) · 2014Article
- Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm.PloS one · 2013Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundAlthough the use of clustering methods has rapidly become one of the standard computational approaches in the literature of microarray gene expression data analysis, little attention has been paid to uncertainty in the results obtained.
resultsWe present an R/Bioconductor port of a fast novel algorithm for Bayesian agglomerative hierarchical clustering and demonstrate its use in clustering gene expression microarray data. The method performs bottom-up hierarchical clustering, using a Dirichlet Process (infinite mixture) to model uncertainty in the data and Bayesian model selection to decide at each step which clusters to merge.
conclusionBiologically plausible results are presented from a well studied data set: expression profiles of A. thaliana subjected to a variety of biotic and abiotic stresses. Our method avoids several limitations of traditional methods, for example how many clusters there should be and how to choose a principled distance metric.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.