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Dries Vaneechoutte

dblp:157/4086 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › network bioinformatics › biological network analysis › gene co-expression network analysis
co-expression network construction
0.412019
Curse: building expression atlases and co-expression networks from public RNA-Seq data · Bioinform. 2019
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis
0.412019
Curse: building expression atlases and co-expression networks from public RNA-Seq data · Bioinform. 2019
Bioinformatics and computational biology
transcriptomics
0.412019
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
YearPublicationVenuePosition
2019 Curse: building expression atlases and co-expression networks from public RNA-Seq data
abstract
SUMMARY: 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