Demo Data from EDBT 2026 / reviewers in the wild / expert
Brett Thomas
dblp:116/4546
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2012
—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 › functional genomics › functional enrichment analysis
gene set enrichment analysis |
0.1 | 1 | 2012 | INRICH: interval-based enrichment analysis for genome-wide association studies · Bioinform. 2012 |
Bioinformatics and computational biology › genomics
genome-wide association study |
0.1 | 1 | 2012 | INRICH: interval-based enrichment analysis for genome-wide association studies · Bioinform. 2012 |
Bioinformatics and computational biology › genomics › genome-wide association study
pathway-based association analysis |
0.1 | 1 | 2012 | INRICH: interval-based enrichment analysis for genome-wide association studies · Bioinform. 2012 |
Methods — techniques the papers use, named apart from their topics
interval-based enrichment · 0.1genomic permutation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | INRICH: interval-based enrichment analysis for genome-wide association studiesabstractSUMMARY: Here we present INRICH (INterval enRICHment analysis), a pathway-based genome-wide association analysis tool that tests for enriched association signals of predefined gene-sets across independent genomic intervals. INRICH has wide applicability, fast running time and, most importantly, robustness to potential genomic biases and confounding factors. Such factors, including varying gene size and single-nucleotide polymorphism density, linkage disequilibrium within and between genes and overlapping genes with similar annotations, are often not accounted for by existing gene-set enrichment methods. By using a genomic permutation procedure, we generate experiment-wide empirical significance values, corrected for the total number of sets tested, implicitly taking overlap of sets into account. By simulation we confirm a properly controlled type I error rate and reasonable power of INRICH under diverse parameter settings. As a proof of principle, we describe the application of INRICH on the NHGRI GWAS catalog. AVAILABILITY: A standalone C++ program, user manual and datasets can be freely downloaded from: http://atgu.mgh.harvard.edu/inrich/. Phil H. Lee, Colm O'Dushlaine, Brett Thomas, Shaun Purcell |
Bioinform. | 3 |