Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 554 software packages, and an active user community. Bioconductor is also available as an Amazon Machine Image (AMI).

References in zbMATH (referenced in 83 articles , 2 standard articles )

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  1. Angelopoulos, Nicos; Abdallah, Samer; Giamas, Georgios: Advances in integrative statistics for logic programming (2016)
  2. Carugo, Oliviero (ed.); Eisenhaber, Frank (ed.): Data mining techniques for the life sciences (2016)
  3. Dasgupta, Nairanjana; Genz, Alan; Lazar, Nicole A.: A look at multiplicity through misclassification (2016)
  4. Mathé, Ewy (ed.); Davis, Sean (ed.): Statistical genomics. Methods and protocols (2016)
  5. Aoshima, Makoto; Yata, Kazuyoshi: Asymptotic normality for inference on multisample, high-dimensional mean vectors under mild conditions (2015)
  6. Lithio, Andrew; Nettleton, Dan: Hierarchical modeling and differential expression analysis for RNA-seq experiments with inbred and hybrid genotypes (2015)
  7. Mayrink, Vinicius D.; Lucas, Joseph E.: Bayesian factor models for the detection of coherent patterns in gene expression data (2015)
  8. Nguyen, Yet; Nettleton, Dan; Liu, Haibo; Tuggle, Christopher K.: Detecting differentially expressed genes with RNA-seq data using backward selection to account for the effects of relevant covariates (2015)
  9. Niemi, Jarad; Mittman, Eric; Landau, Will; Nettleton, Dan: Empirical Bayes analysis of RNA-seq data for detection of gene expression heterosis (2015)
  10. Picardi, Ernesto (ed.): RNA bioinformatics (2015)
  11. Carey, Vincent (ed.); Cook, Dianne (ed.): Four papers on contemporary software design strategies for statistical methodologists (2014)
  12. Caserta, Marco; Voß, Stefan: A hybrid algorithm for the DNA sequencing problem (2014)
  13. Chambers, John M.: Object-oriented programming, functional programming and R (2014)
  14. Datta, Somnath (ed.); Nettleton, Dan (ed.): Statistical analysis of next generation sequencing data (2014)
  15. Gu, Jian-lei; Lu, Yao; Liu, Cong; Lu, Hui: Multiclass classification of sarcomas using pathway based feature selection method (2014)
  16. Hieke, Stefanie; Binder, Harald; Nieters, Alexandra; Schumacher, Martin: minPtest: a resampling based gene region-level testing procedure for genetic case-control studies (2014)
  17. Lawrence, Michael; Morgan, Martin: Scalable genomics with R and bioconductor (2014)
  18. Blocker, Alexander W.; Meng, Xiao-Li: The potential and perils of preprocessing: building new foundations (2013)
  19. Eddelbuettel, Dirk: Seamless R and C++ integration with Rcpp (2013)
  20. Galluccio, Laurent; Michel, Olivier; Comon, Pierre; Kliger, Mark; Hero, Alfred O.: Clustering with a new distance measure based on a dual-rooted tree (2013)

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