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A comparison of four clustering methods for brain expression microarray data

By Alexander L Richards, Peter Holmans, Michael C O'Donovan, Michael J Owen and Lesley Jones
Topics: Research Article
Publisher: BioMed Central
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Provided by: PubMed Central

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  2. (2005). AJ: Systematic survey reveals general applicability of "guilt-by-association" within gene coexpression networks.
  3. (2005). Allison DB: Reproducible Clusters from Microarray Research: Whither?
  4. (2006). B: An online database for brain disease research.
  5. (2002). Barkai N: Revealing modular organization in the yeast transcriptional network. Nature Genetics
  6. (2008). Barres BA: A transcriptome database for astrocytes, neurons and oligodendrocytes: a new resource for understanding brain development and function.
  7. (2006). Clustering microarray gene expression data using weighted Chinese restaurant process. Bioinformatics
  8. Databank: Brain Tissue Gene Expression Repository.
  9. (2004). Differential expression of mitogen-activated protein kinases and immediate early genes fos and jun in thalamus in schizophrenia.
  10. (2004). Distributed computing in practice: the Condor experience. Concurrency and Computation: Practice and Experience
  11. (2005). Draghici S: Ontological analysis of gene expression data: current tools, limitations, and open problems. Bioinformatics
  12. (2003). Fuzzy C-means method for clustering microarray data. Bioinformatics
  13. (2005). Hénaut A: Comments on selected fundamental aspects of microarray analysis.
  14. (2002). Hogenesch JB: Large-scale analysis of the human and mouse transcriptomes.
  15. (2003). Iterative signature algorithm for the analysis of large-scale gene expression data.
  16. (2005). Meng F: Evolving gene/ transcript definitions significantly alter the interpretation of Gene Chip data. Nucleic Acids Research
  17. (2006). Microarray Data Analysis: from disarray to consolidation to consensus. Nature Reviews Genetics
  18. (2004). Miyano S: Open Source Clustering Software. Bioinformatics
  19. (2006). NCBI GEO: mining tens of millions of expression profiles – database and tools update.
  20. (2005). NS: Finding regulatory modules through large-scale gene expression analysis. Bioinformatics
  21. (2007). Penalized and weighted K-means for clustering with scattered objects and prior information in highthroughput biological data. Bioinformatics
  22. Project for Statistical Computing []. R: A language and environment for statistical computing
  23. (2008). Rare Structural Variants Disrupt Multiple Genes in Neurodevelopmental Pathways in Schizophrenia. Science
  24. (2005). Searching for differentially expressed gene combinations. Genome Biology
  25. (2004). Speed TP: GOstat: Find statistically overrepresented Gene Ontologies within a group of genes. Bioinformatics
  26. (2003). TP: A comparison of normalization methods for high density oligonucleotide array data based on bias and variance. Bioinformatics
  27. (2006). Tseng GC: Evaluation and comparison of gene clustering methods in microarray analysis. Bioinformatics
  28. vegan: Community Ecology Package,
  29. (2007). VM: Gene expression profiles in rat brain disclose CNS signature genes and regional patterns of functional specialisation.
  30. (1979). Wong MA: A K-Means Clustering Algorithm. Applied Statistics
  31. (2006). Y-X: Comparisons of Graphstructure Clustering Methods for Gene Expression Data. Acta Biochimica et Biophysica Sinica
  32. (2006). Yang PC: CRSD: a comprehensive web server for composite regulatory signature discovery. Nucleic Acids Research
  33. (2006). Zitzer E: A systematic comparison and evaluation of biclustering methods for gene expression data. Bioinformatics

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