Bioconductor

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 328 articles , 2 standard articles )

Showing results 1 to 20 of 328.
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  1. Bickel, David R.: Confidence distributions and empirical Bayes posterior distributions unified as distributions of evidential support (2022)
  2. Dong, Ping; Lin, Lu: Neyman’s truncation test for two-sample means under high dimensional setting (2022)
  3. Jun Woo, Jinhua Wang: bbl: Boltzmann Bayes Learner for High-Dimensional Inference with Discrete Predictors in R (2022) not zbMATH
  4. Milad, Mohamed; Olbricht, Gayla R.: Testing differentially methylated regions through functional principal component analysis (2022)
  5. Mou, Xichen; Zhang, Hongmei; Arshad, S. Hasan: Identifying intergenerational patterns of correlated methylation sites (2022)
  6. Ozan Cinar, Wolfgang Viechtbauer: The poolr Package for Combining Independent and Dependent p Values (2022) not zbMATH
  7. Toby Dylan Hocking, Guillem Rigaill, Paul Fearnhead, Guillaume Bourque: Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic Data (2022) not zbMATH
  8. Akalin, Altuna: Computational genomics with R. With the assistance of Verdan Franke, Bora Uyar and Jonathan Ronen (2021)
  9. Byrd, Michael; Nghiem, Linh H.; McGee, Monnie: Bayesian regularization of Gaussian graphical models with measurement error (2021)
  10. Chulián, Salvador; Martínez-Rubio, Álvaro; Marciniak-Czochra, Anna; Stiehl, Thomas; Goñi, Cristina Blázquez; Rodríguez Gutiérrez, Juan Francisco; Ramírez Orellana, Manuel; Castillo Robleda, Ana; Pérez-García, Víctor M.; Rosa, María: Dynamical properties of feedback signalling in B lymphopoiesis: a mathematical modelling approach (2021)
  11. Doğru, Fatma Zehra; Arslan, Olcay: Finite mixtures of skew Laplace normal distributions with random skewness (2021)
  12. Jacques Serizay: Generating fragment density plots in R/Bioconductor with VplotR (2021) not zbMATH
  13. Lim, David K.; Rashid, Naim U.; Ibrahim, Joseph G.: Model-based feature selection and clustering of RNA-seq data for unsupervised subtype discovery (2021)
  14. Mohammed, Shariq; Bharath, Karthik; Kurtek, Sebastian; Rao, Arvind; Baladandayuthapani, Veerabhadran: RADIOHEAD: radiogenomic analysis incorporating tumor heterogeneity in imaging through densities (2021)
  15. Shanmugam, Ramalingam: Book review of: J. R. Gonzalez and A. Caceres, Omic association studies with and bioconductor. (2021)
  16. Signorelli, Mirko; Spitali, Pietro; Tsonaka, Roula: Poisson-Tweedie mixed-effects model: a flexible approach for the analysis of longitudinal RNA-seq data (2021)
  17. Tian, Tian; Cheng, Ruihua; Wei, Zhi: An empirical Bayes change-point model for transcriptome time-course data (2021)
  18. Zhao, Sihai Dave: Simultaneous estimation of normal means with side information (2021)
  19. de Almeida, Rita M. C.; se Souza, Lars L. S.; Morais, Diego; Dalmolin, Rodrigo J. S.: Transcriptograms: a genome-wide gene expression analysis method (2020)
  20. Granata, Ilaria; Guarracino, Mario R.; Kalyagin, Valery A.; Maddalena, Lucia; Manipur, Ichcha; Pardalos, Panos M.: Model simplification for supervised classification of metabolic networks (2020)

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