Demo Data from EDBT 2026 / reviewers in the wild / expert
Stephen Eyre
dblp:54/8886
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2011
0000-0002-1251-6974ORCID · reported
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 › genomics › genome-wide association study
causal variant prioritization |
0.1 | 1 | 2011 | ASSIMILATOR: a new tool to inform selection of associated genetic variants for functional studies · Bioinform. 2011 |
Bioinformatics and computational biology › statistical genetics
fine-mapping |
0.1 | 1 | 2011 | ASSIMILATOR: a new tool to inform selection of associated genetic variants for functional studies · Bioinform. 2011 |
Bioinformatics and computational biology › genomics
genome-wide association study |
0.1 | 1 | 2011 | ASSIMILATOR: a new tool to inform selection of associated genetic variants for functional studies · Bioinform. 2011 |
Bioinformatics and computational biology › functional genomics
functional annotation integration |
0.0 | 1 | 2011 | ASSIMILATOR: a new tool to inform selection of associated genetic variants for functional studies · Bioinform. 2011 |
Methods — techniques the papers use, named apart from their topics
data integration · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | ASSIMILATOR: a new tool to inform selection of associated genetic variants for functional studiesabstractMOTIVATION: Fine-mapping experiments from genome-wide association studies (GWAS) are underway for many complex diseases. These are likely to identify a number of putative causal variants, which cannot be separated further in terms of strength of genetic association due to linkage disequilibrium. The challenge will be selecting which variant to prioritize for subsequent expensive functional studies. A wealth of functional information generated from wet lab experiments now exists but cannot be easily interrogated by the user. Here, we describe a program designed to quickly assimilate this data called ASSIMILATOR and validate the method by interrogating two regions to show its effectiveness. AVAILABILITY: http://www.medicine.manchester.ac.uk/musculoskeletal/research/arc/genetics/bioinformatics/assimilator/. Paul Martin 0005, Anne Barton, Stephen Eyre |
Bioinform. | 3 |