Demo Data from EDBT 2026 / reviewers in the wild / expert
Rebecca Brosens
dblp:85/7063
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · none
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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › gene expression analysis › microarray data analysis
array comparative genomic hybridization |
0.1 | 1 | 2009 | Smoothing waves in array CGH tumor profiles · Bioinform. 2009 |
Bioinformatics and computational biology › genomics
breakpoint detection |
0.1 | 1 | 2009 | Smoothing waves in array CGH tumor profiles · Bioinform. 2009 |
Bioinformatics and computational biology › cancer genomics › chromosomal aberration detection
copy number aberration detection |
0.1 | 1 | 2009 | Smoothing waves in array CGH tumor profiles · Bioinform. 2009 |
Methods — techniques the papers use, named apart from their topics
smoothing · 0.1regression · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | Smoothing waves in array CGH tumor profilesabstractMOTIVATION: Many high-resolution array comparative genomic hybridization tumor profiles contain a wave bias, which makes accurate detection of breakpoints in such profiles more difficult. RESULTS: An efficient and highly effective algorithm that largely removes the wave bias from tumor profiles by regressing the tumor profile data on data of profiles from the clinical genetics practice. Results are illustrated on two independent datasets. The algorithm is shown to be robust against the presence of true copy number aberrations. Moreover, the smoothed profiles are able to recapitulate the aberration location and signal for simulated tumor profiles. AVAILABILITY: Easy-to-use R scripts, user instructions and data are available from http://www.few.vu.nl/~mavdwiel/nowaves.html. SUPPLEMENTARY INFORMATION: Supplementary information are available at Bioinformatics online. Mark A. van de Wiel, Rebecca Brosens, Paul H. C. Eilers, Candy Kumps, Gerrit Meijer, Björn Menten, Erik Sistermans, Frank Speleman, Marieke E. Timmerman, Bauke Ylstra |
Bioinform. | 2 |