Demo Data from EDBT 2026 / reviewers in the wild / expert
Katja Koeppen
dblp:209/7973
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2017
0000-0003-1094-0621ORCID · reported
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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
data mining |
0.3 | 1 | 2017 | ScanGEO: parallel mining of high-throughput gene expression data · Bioinform. 2017 |
Bioinformatics and computational biology › gene expression analysis
differential expression analysis |
0.3 | 1 | 2017 | ScanGEO: parallel mining of high-throughput gene expression data · Bioinform. 2017 |
Bioinformatics and computational biology
gene expression |
0.3 | 1 | 2017 | ScanGEO: parallel mining of high-throughput gene expression data · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
shiny · 0.3r · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | ScanGEO: parallel mining of high-throughput gene expression dataabstractSUMMARY: Current options to mine publicly available gene expression data deposited in NCBI's gene expression omnibus (GEO), such as the GEO web portal and related applications, are optimized to reanalyze a single study, or search for a single gene, and therefore require manual intervention to reanalyze multiple studies for user-specified gene sets. ScanGEO is a simple, user-friendly Shiny web application designed to identify differentially expressed genes across all GEO studies matching user-specified criteria, for a flexible set of genes, visualize results and provide summary statistics and other reports using a single command. AVAILABILITY AND IMPLEMENTATION: The ScanGEO source code is written in R and implemented as a Shiny app that can be freely accessed at http://scangeo.dartmouth.edu/ScanGEO/. For users who would like to run a local instantiation of the app, the R source code is available under a GNU GPLv3 license at https://github.com/StantonLabDartmouth/AppScanGEO. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Katja Koeppen, Bruce A. Stanton, Thomas H. Hampton |
Bioinform. | 1 |