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Irizarry R, et al. (2015) Biomedical Data Science. Course Notes, EdX PH525.1x.
Huber W, et al. (2015) Orchestrating high-throughput genomic analysis with Bioconductor. Nature Methods 12:115-121; doi:10.1038/nmeth.3252 (full-text free with registration). PMC4509590
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, and Smyth, GK (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucl. Acids Res; doi:10.1093/nar/gkv007
Love M, Huber W, and Anders S. (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 15:550; doi:10.1186/s13059-014-0550-8
Lawrence M, Huber W, Pagès H, Aboyoun P, Carlson M, et al. (2013) Software for Computing and Annotating Genomic Ranges. PLoS Comput Biol 9(8): e1003118. doi: 10.1371/journal.pcbi.1003118

Recent

20 most recent PubMed and PubMed Central citations mentioning "Bioconductor". For a complete list, go to PubMed and PubMed Central. Last updated 2015-08-31T18:20:07-04:00.

Amrani KE, Stachelscheid H, Lekschas F, Kurtz A, Andrade-Navarro MA. MGFM: a novel tool for detection of tissue and cell specific marker genes from microarray gene expression data BMC Genomics, 16(1), pp. 645. doi:10.1186/s12864-015-1785-9 (28 August 2015)
Fang L, Sun D, Xu Z, He J, Qi S, Chen X, Chew W, Liu J. Transcriptomic analysis of a moderately growing subisolate Botryococcus braunii 779 (Chlorophyta) in response to nitrogen deprivation Biotechnol Biofuels, 8, pp. 130. doi:10.1186/s13068-015-0307-y (28 August 2015)
Murrell DS, Cortes-Ciriano I, van Westen GJ, Stott IP, Bender A, Malliavin TE, Glen RC. Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules J Cheminform, 7, pp. 45. doi:10.1186/s13321-015-0086-2 (28 August 2015)
Turner JA, Bolen CR, Blankenship DM. Quantitative gene set analysis generalized for repeated measures, confounder adjustment, and continuous covariates BMC Bioinformatics, 16(1), pp. 272. doi:10.1186/s12859-015-0707-9 (28 August 2015)
Yao S, Yoo S, Yu D. Prior knowledge driven Granger causality analysis on gene regulatory network discovery BMC Bioinformatics, 16(1), pp. 273. doi:10.1186/s12859-015-0710-1 (28 August 2015)
Brahimi-Horn MC, Giuliano S, Saland E, Lacas-Gervais S, Sheiko T, Pelletier J, Bourget I, Bost F, Féral C, Boulter E, Tauc M, Ivan M, Garmy-Susini B, Popa A, Mari B, Sarry JE, Craigen WJ, Pouysségur J, Mazure NM. Knockout of Vdac1 activates hypoxia-inducible factor through reactive oxygen species generation and induces tumor growth by promoting metabolic reprogramming and inflammation Cancer Metab, 3, pp. 8. doi:10.1186/s40170-015-0133-5 (26 August 2015)
Camargo RD, Herai RH, Santos LN, Bento FM, Lima JE, Marques-Souza H, Figueira A. De novo transcriptome assembly and analysis to identify potential gene targets for RNAi-mediated control of the tomato leafminer (Tuta absoluta) BMC Genomics, 16(1), pp. 635. doi:10.1186/s12864-015-1841-5 (26 August 2015)
Bennett M, Evans KE, Yu S, Teng Y, Webster RM, Powell J, Waters R, Reed SH. Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure Sci Rep, 5, pp. 13395. doi:10.1038/srep13395 (26 August 2015)
Pavlopoulos GA, Malliarakis D, Papanikolaou N, Theodosiou T, Enright AJ, Iliopoulos I. Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future Gigascience, 4, pp. 38. doi:10.1186/s13742-015-0077-2 (25 August 2015)
Bellesi M, de Vivo L, Tononi G, Cirelli C. Effects of sleep and wake on astrocytes: clues from molecular and ultrastructural studies BMC Biol, 13, pp. 66. doi:10.1186/s12915-015-0176-7 (25 August 2015)
Bohler A, Eijssen LM, van Iersel MP, Leemans C, Willighagen EL, Kutmon M, Jaillard M, Evelo CT. Automatically visualise and analyse data on pathways using PathVisioRPC from any programming environment BMC Bioinformatics, 16(1), pp. 267. doi:10.1186/s12859-015-0708-8 (23 August 2015)
Curry E, Green I, Chapman-Rothe N, Shamsaei E, Kandil S, Cherblanc FL, Payne L, Bell E, Ganesh T, Srimongkolpithak N, Caron J, Li F, Uren AG, Snyder JP, Vedadi M, Fuchter MJ, Brown R. Dual EZH2 and EHMT2 histone methyltransferase inhibition increases biological efficacy in breast cancer cells Clin Epigenetics, 7(1), pp. 84. doi:10.1186/s13148-015-0118-9 (21 August 2015)
Everson TM, Lyons G, Zhang H, Soto-Ramírez N, Lockett GA, Patil VK, Merid SK, Sӧderhӓll C, Melén E, Holloway JW, Arshad SH, Karmaus W. DNA methylation loci associated with atopy and high serum IgE: a genome-wide application of recursive Random Forest feature selection Genome Med, 7(1), pp. 89. doi:10.1186/s13073-015-0213-8 (21 August 2015)
Castiglioni L, Colazzo F, Fontana L, Colombo GI, Piacentini L, Bono E, Milano G, Paleari S, Palermo A, Guerrini U, Tremoli E, Sironi L. Evaluation of Left Ventricle Function by Regional Fractional Area Change (RFAC) in a Mouse Model of Myocardial Infarction Secondary to Valsartan Treatment PLoS One, 10(8), pp. e0135778. doi:10.1371/journal.pone.0135778 (20 August 2015)
Pacholewska A, Jagannathan V, Drögemüller M, Klukowska-Rötzler J, Lanz S, Hamza E, Dermitzakis ET, Marti E, Leeb T, Gerber V. Impaired Cell Cycle Regulation in a Natural Equine Model of Asthma PLoS One, 10(8), pp. e0136103. doi:10.1371/journal.pone.0136103 (20 August 2015)
Lee J, Prokopec SD, Watson JD, Sun RX, Pohjanvirta R, Boutros PC. Male and female mice show significant differences in hepatic transcriptomic response to 2,3,7,8-tetrachlorodibenzo-p-dioxin BMC Genomics, 16(1), pp. 625. doi:10.1186/s12864-015-1840-6 (20 August 2015)
Ma X, Ezer D, Navarro C, Adryan B. Reliable scaling of position weight matrices for binding strength comparisons between transcription factors BMC Bioinformatics, 16(1), pp. 265. doi:10.1186/s12859-015-0666-1 (20 August 2015)
Vincent KM, Findlay SD, Postovit LM. Assessing breast cancer cell lines as tumour models by comparison of mRNA expression profiles Breast Cancer Res, 17(1), pp. 114. doi:10.1186/s13058-015-0613-0 (20 August 2015)
Lun AT, Smyth GK. diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C data. BMC Bioinformatics, 16(1), pp. 258. doi:10.1186/s12859-015-0683-0 (19 August 2015)
Nezami Ranjbar MR, Poto CD, Wang Y, Ressom HW. SIMAT: GC-SIM-MS data analysis tool. BMC Bioinformatics, 16(1), pp. 259. doi:10.1186/s12859-015-0681-2 (19 August 2015)

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