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Citations per year

Number of citations per year for the bioinformatics software tool rcellminer

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rcellminer specifications


Unique identifier OMICS_10816
Name rcellminer
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU Lesser General Public License version 3.0
Computer skills Advanced
Version 2.2.0
Stability Stable
methods, stats, RColorBrewer, gplots, parallel, BiocGenerics, Biobase, utils, testthat, BiocStyle, ggplot2, knitr, sqldf, foreach, R(>=3.2), stringr, shiny, rcdk, doSNOW, glmnet, jsonlite, d3heatmap, fingerprint, rcellminerData
Maintained Yes


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Publication for rcellminer

rcellminer citations


Characterizing Cancer Drug Response and Biological Correlates: A Geometric Network Approach

Sci Rep
PMCID: 5913269
PMID: 29686393
DOI: 10.1038/s41598-018-24679-3

[…] ration resulting in a 50% reduction in the net protein increase during drug incubation as compared with the same increase in control cells,. Normalized (−log10) GI50 was retrieved using the R package rcellminer. This package complements the functionality of CellMiner by providing programmatic data access as well as analysis and visualization tool. By computing the Spearman’s correlation between th […]


Using Pharmacogenomic Databases for Discovering Patient Target Genes and Small Molecule Candidates to Cancer Therapy

Front Pharmacol
PMCID: 5040751
PMID: 27746730
DOI: 10.3389/fphar.2016.00312

[…] ns between samples (). The database serves as reference to query the abundance and distribution of proteins in each cell line as well as protein signature for drug sensitivity and resistance (; ).The rcellminer is an R package that provides a wide range of functionality to help R users to access and explore molecular profiling and drug response data in the NCI-60 CellMiner platform (). This tool a […]

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rcellminer institution(s)
Computer Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Developmental Therapeutic Branch, Center for Cancer Research, NCI, NIH, Bethesda, MD, USA; Centro de Estudos em Células Tronco, Terapia Celular e Genética Toxicológica, Programa de Pós-Graduação em Farmácia, Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil; Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
rcellminer funding source(s)
This work was supported by the NIH grants: MSKCC Genome Data Analysis Center grant (U24 CA143840), the Ruth L. Kirschstein National Research Service Award (F32 CA192901) and by the Center for Cancer Research, Intramural Program of the National Cancer Institute (Z01 BC006150).

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