The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
MSnbase-an R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation
Open accessAbstract
Summary: MSnbase is an R/Bioconductor package for the analysis of quantitative proteomics experiments that use isobaric tagging. It provides an exploratory data analysis framework for reproducible research, allowing raw data import, quality control, visualization, data processing and quantitation. MSnbase allows direct integration of quantitative proteomics data with additional facilities for statistical analysis provided by the Bioconductor project. Availability: MSnbase is implemented in R (version ≥2.13.0) and available at the Bioconductor web site (http://www.bioconductor.org/). Vignettes outlining typical workflows, input/output capabilities and detailing underlying infrastructure are included in the package. Contact: lg390@cam.ac.uk Supplementary information: Supplementary data are available from Bioinformatics online.
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Bioconductor: open software development for computational biology and bioinformatics
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The minimum information about a proteomics experiment (MIAPE)
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Self-citationAddressing Accuracy and Precision Issues in iTRAQ Quantitation
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Self-citationMass spectrometry in high-throughput proteomics: ready for the big time
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Self-citationChoi, M., Chang, C.-Y., Clough, T., Broudy, D., Killeen, T., MacLean, B., & Vitek, O. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu305 · Cited by 1,035
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Metadata
- Authors
- Gatto, L., & Lilley, K. S.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-11-22
- Volume
- 28
- Issue
- 2
- Pages
- 288-289
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2106839391
- Cited by
- 377
- References
- 9
- FWCI
- 3.28
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Gatto, L., & Lilley, K. S. (2012). MSnbase-an R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics. https://doi.org/10.1093/bioinformatics/btr645
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