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pRRophetic: an R package for prediction of clinical chemotherapeutic response from tumor gene expression levels

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pRRophetic: an R package for prediction of clinical chemotherapeutic response from tumor gene expression levels (English)

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1 reference

2

Nancy Cox

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author name string

Paul Geeleher

series ordinal

1

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R Stephanie Huang

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3

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language of work or name

English

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publication date

2014

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published in

PLOS One

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volume

9

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issue

9

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page(s)

e107468

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copyright license

Creative Commons Attribution 4.0 International

start time

17 September 2014

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April 2022 Public Data File from Crossref

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copyrighted

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describes a project that uses

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The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

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PubMed Central

reference URL

https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=4167990

retrieved

7 April 2017

Systematic identification of genomic markers of drug sensitivity in cancer cells

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PubMed Central

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https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=4167990

retrieved

7 April 2017

Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines

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PubMed Central

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https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=4167990

retrieved

29 September 2017

Inconsistency in large pharmacogenomic studies

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PubMed Central

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https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=4167990

retrieved

29 September 2017

Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib

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https://api.crossref.org/works/10.1371%2FJOURNAL.PONE.0107468

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21 January 2018

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DOI

10.1371/JOURNAL.PONE.0107468

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PubMed publication ID

25229481

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ResearchGate publication ID

265791443

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(Q28543035)

pRRophetic: an R package for prediction of clinical chemotherapeutic response from tumor gene expression levels

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