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Frank J. Sørensen

dblp:80/1832 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2007
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › cancer genomics
copy number analysis
0.112007
SNPTools: a software tool for visualization and analysis of microarray data · Bioinform. 2007
Bioinformatics and computational biology › cancer genomics › chromosomal aberration detection
loss of heterozygosity detection
0.112007
SNPTools: a software tool for visualization and analysis of microarray data · Bioinform. 2007
Bioinformatics and computational biology › gene expression analysis
microarray data analysis
0.112007
SNPTools: a software tool for visualization and analysis of microarray data · Bioinform. 2007
Bioinformatics and computational biology › genomics
genome visualization
0.012007
SNPTools: a software tool for visualization and analysis of microarray data · Bioinform. 2007

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

segmentation · 0.1intensity analysis · 0.1
YearPublicationVenuePosition
2007 SNPTools: a software tool for visualization and analysis of microarray data
abstract
SUMMARY: We have created a software tool, SNPTools, for analysis and visualization of microarray data, mainly SNP array data. The software can analyse and find differences in intensity levels between groups of arrays and identify segments of SNPs (genes, clones), where the intensity levels differ significantly between the groups. In addition, SNPTools can show jointly loss-of-heterozygosity (LOH) data (derived from genotypes) and intensity data for paired samples of tumour and normal arrays. The output graphs can be manipulated in various ways to modify and adjust the layout. A wizard allows options and parameters to be changed easily and graphs replotted. All output can be saved in various formats, and also re-opened in SNPTools for further analysis. For explorative use, SNPTools allows various genome information to be loaded onto the graphs. AVAILABILITY: The software, example data sets and tutorials are freely available from http://www.birc.au.dk/snptools
Frank J. Sørensen, Claus L. Andersen, Carsten Wiuf
Bioinform.1