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Ana Dopazo

dblp:12/1512 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2007
0000-0002-4910-1684ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
gene expression analysis
0.112007
Codelink: an R package for analysis of GE healthcare gene expression bioarrays · Bioinform. 2007
Bioinformatics and computational biology › gene expression analysis
microarray data analysis
0.112007
Codelink: an R package for analysis of GE healthcare gene expression bioarrays · Bioinform. 2007

Methods — techniques the papers use, named apart from their topics

statistical analysis · 0.1
YearPublicationVenuePosition
2007 Codelink: an R package for analysis of GE healthcare gene expression bioarrays
abstract
MOTIVATION: Microarray-based expression profiles have become a standard methodology in any high-throughput analysis. Several commercial platforms are available, each with its strengths and weaknesses. The R platform for statistical analysis and graphics is a powerful environment for the analysis of microarray data, because it has many integrated statistical methods available as well as the specialized microarray analysis project Bioconductor. Many packages have been added in the last few years increasing the range of possible analysis. Here, we report the availability of a package for reading and analyzing data from GE Healthcare Gene Expression Bioarrays within the R environment. AVAILABILITY: The software is implemented in the R language, is open source and available for download free of charge through the Bioconductor (http://www.bioconductor.org) project.
Diego Diez, Rebeca Alvarez, Ana Dopazo
Bioinform.3