Demo Data from EDBT 2026 / reviewers in the wild / expert
Raymond K. Auerbach
dblp:132/3475
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author
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
gene function analysis |
0.2 | 1 | 2013 | Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool · Bioinform. 2013 |
Bioinformatics and computational biology › epigenomics
ChIP-seq analysis |
0.0 | 1 | 2013 | Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool · Bioinform. 2013 |
Bioinformatics and computational biology › gene regulation › transcription factor binding
transcription factor binding analysis |
0.0 | 1 | 2013 | Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool · Bioinform. 2013 |
Methods — techniques the papers use, named apart from their topics
statistical enrichment analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance toolabstractMOTIVATION: Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses. IMPLEMENTATION: The ENCODE ChIP-Seq Significance Tool is written in JavaScript on the client side and has been tested on Google Chrome, Apple Safari and Mozilla Firefox browsers. Server-side scripts are written in PHP and leverage R and a MySQL database. The tool is available at http://encodeqt.stanford.edu. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online. Raymond K. Auerbach, Atul J. Butte |
Bioinform. | 1 |