Demo Data from EDBT 2026 / reviewers in the wild / expert
Dries Vaneechoutte
dblp:157/4086
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0002-8975-2801ORCID · 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 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › network bioinformatics › biological network analysis › gene co-expression network analysis
co-expression network construction |
0.4 | 1 | 2019 | Curse: building expression atlases and co-expression networks from public RNA-Seq data · Bioinform. 2019 |
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis |
0.4 | 1 | 2019 | Curse: building expression atlases and co-expression networks from public RNA-Seq data · Bioinform. 2019 |
Bioinformatics and computational biology
transcriptomics |
0.4 | 1 | 2019 | Curse: building expression atlases and co-expression networks from public RNA-Seq data · Bioinform. 2019 |
Methods — techniques the papers use, named apart from their topics
data curation · 0.4RNA-Seq processing pipeline · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Curse: building expression atlases and co-expression networks from public RNA-Seq dataabstractSUMMARY: Public RNA-Sequencing (RNA-Seq) datasets are a valuable resource for transcriptome analyses, but their accessibility is hindered by the imperfect quality and presentation of their metadata and by the complexity of processing raw sequencing data. The Curse suite was created to alleviate these problems. It consists of an online curation tool named Curse to efficiently build compendia of experiments hosted on the Sequence Read Archive, and a lightweight pipeline named Prose to download and process the RNA-Seq data into expression atlases and co-expression networks. Curse networks showed improved linking of functionally related genes compared to the state-of-the-art. AVAILABILITY AND IMPLEMENTATION: Curse, Prose and their manuals are available at http://bioinformatics.psb.ugent.be/webtools/Curse/. Prose was implemented in Java. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Dries Vaneechoutte, Klaas Vandepoele |
Bioinform. | 1 |