Demo Data from EDBT 2026 / reviewers in the wild / expert
Joseph McQuown
dblp:45/1426
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2007
—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 |
0.1 | 1 | 2007 | Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data · Bioinform. 2007 |
Bioinformatics and computational biology › gene expression analysis
microarray data analysis |
0.1 | 1 | 2007 | Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data · Bioinform. 2007 |
Bioinformatics and computational biology › epigenomics
ChIP-chip analysis |
0.0 | 1 | 2007 | Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data · Bioinform. 2007 |
Methods — techniques the papers use, named apart from their topics
adaptive multiscale algorithm · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip dataabstractUNLABELLED: We present a fast, versatile and adaptive-multiscale algorithm for analyzing a wide-variety of DNA microarray data. Its primary application is in normalization of array data as well as subsequent identification of 'enriched targets', e.g. differentially expressed genes in expression profiling arrays and enriched sites in ChIP-on-chip experimental data. We show how to accommodate the unique characteristics of ChIP-on-chip data, where the set of 'enriched targets' is large, asymmetric and whose proportion to the whole data varies locally. SUPPLEMENTARY INFORMATION: Supplementary figures, related preprint, free software as well as our raw DNA microarray data with PCR validations are available at http://www.math.umn.edu/~lerman/supp/bioinfo06 as well as Bioinformatics online. Gilad Lerman, Joseph McQuown, Alexandre Blais, Brian D. Dynlacht, Guangliang Chen, Bud Mishra |
Bioinform. | 2 |