Demo Data from VLDB 2026 / reviewers in the wild / expert
Joshua Bowden
dblp:261/4136
· 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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
genomics |
0.4 | 1 | 2020 | Eagle: multi-locus association mapping on a genome-wide scale made routine · Bioinform. 2020 |
Bioinformatics and computational biology › statistical genetics › genetic association study
multi-locus association mapping |
0.4 | 1 | 2020 | Eagle: multi-locus association mapping on a genome-wide scale made routine · Bioinform. 2020 |
Bioinformatics and computational biology › genomics
genome-wide association study |
0.1 | 1 | 2020 | Eagle: multi-locus association mapping on a genome-wide scale made routine · Bioinform. 2020 |
Methods — techniques the papers use, named apart from their topics
statistical association testing · 0.4simulation study · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Eagle: multi-locus association mapping on a genome-wide scale made routineabstractMOTIVATION: We present Eagle, a new method for multi-locus association mapping. The motivation for developing Eagle was to make multi-locus association mapping 'easy' and the method-of-choice. Eagle's strengths are that it (i) is considerably more powerful than single-locus association mapping, (ii) does not suffer from multiple testing issues, (iii) gives results that are immediately interpretable and (iv) has a computational footprint comparable to single-locus association mapping. RESULTS: By conducting a large simulation study, we will show that Eagle finds true and avoids false single-nucleotide polymorphism trait associations better than competing single- and multi-locus methods. We also analyze data from a published mouse study. Eagle found over 50% more validated findings than the state-of-the-art single-locus method. AVAILABILITY AND IMPLEMENTATION: Eagle has been implemented as an R package, with a browser-based Graphical User Interface for users less familiar with R. It is freely available via the CRAN website at https://cran.r-project.org. Videos, Quick Start guides, FAQs and Demos are available via the Eagle website http://eagle.r-forge.r-project.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Andrew W. George, Arunas Verbyla, Joshua Bowden |
Bioinform. | 3 |