Demo Data from EDBT 2026 / reviewers in the wild / expert
Richard Crooijmans
dblp:258/2760
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—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 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › statistical genetics › association analysis
copy number variant association |
0.4 | 1 | 2020 | CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes · Bioinform. 2020 |
Bioinformatics and computational biology
genomics |
0.4 | 1 | 2020 | CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes · Bioinform. 2020 |
Bioinformatics and computational biology › genomics
structural variation |
0.4 | 1 | 2020 | CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes · Bioinform. 2020 |
Bioinformatics and computational biology › genomics
genome-wide association study |
0.1 | 1 | 2020 | CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes · Bioinform. 2020 |
Methods — techniques the papers use, named apart from their topics
statistical association analysis · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypesabstractSUMMARY: Copy number variation (CNV) is a major type of structural genomic variation that is increasingly studied across different species for association with diseases and production traits. Established protocols for experimental detection and computational inference of CNVs from SNP array and next-generation sequencing data are available. We present the CNVRanger R/Bioconductor package which implements a comprehensive toolbox for structured downstream analysis of CNVs. This includes functionality for summarizing individual CNV calls across a population, assessing overlap with functional genomic regions, and genome-wide association analysis with gene expression and quantitative phenotypes. AVAILABILITY AND IMPLEMENTATION: http://bioconductor.org/packages/CNVRanger. Vinícius da Silva, Marcel Ramos, Martien Groenen, Richard Crooijmans, Anna Johansson, Luciana C. A. Regitano, Luiz Coutinho, Ralf Zimmer, Levi Waldron, Ludwig Geistlinger |
Bioinform. | 4 |