Demo Data from EDBT 2026 / reviewers in the wild / expert
Sebastian Bartschat
dblp:51/9005
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2014
0000-0001-7935-9582ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 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
2 papers |
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
comparative genomics |
0.2 | 1 | 2014 | snoStrip: a snoRNA annotation pipeline · Bioinform. 2014 |
Bioinformatics and computational biology › genome annotation
non-coding RNA annotation |
0.2 | 1 | 2014 | snoStrip: a snoRNA annotation pipeline · Bioinform. 2014 |
Bioinformatics and computational biology › RNA biology
non-coding RNA |
0.1 | 1 | 2011 | PLEXY: efficient target prediction for box C/D snoRNAs · Bioinform. 2011 |
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics › RNA structure prediction
RNA secondary structure prediction |
0.1 | 1 | 2014 | snoStrip: a snoRNA annotation pipeline · Bioinform. 2014 |
Methods — techniques the papers use, named apart from their topics
sequence conservation analysis · 0.2secondary structure prediction · 0.2motif detection · 0.2thermodynamic modeling · 0.1dynamic programming · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | snoStrip: a snoRNA annotation pipelineabstractMOTIVATION: Although small nucleolar RNAs form an important class of non-coding RNAs, no comprehensive annotation efforts have been undertaken, presumably because the task is complicated by both the large number of distinct small nucleolar RNA families and their relatively rapid pace of sequence evolution. RESULTS: With snoStrip we present an automatic annotation pipeline developed specifically for comparative genomics of small nucleolar RNAs. It makes use of sequence conservation, canonical box motifs as well as secondary structure and predicts putative targets. AVAILABILITY AND IMPLEMENTATION: The snoStrip web service and the download version is available at http://snostrip.bioinf.uni-leipzig.de/ Sebastian Bartschat, Stephanie Kehr, Hakim Tafer, Peter F. Stadler, Jana Schor |
Bioinform. | 1 |
| 2011 | PLEXY: efficient target prediction for box C/D snoRNAsabstractMOTIVATION: Small nucleolar RNAs (snoRNAs) are an abundant class of non-coding RNAs with a wide variety of cellular functions including chemical modification of RNA, telomere maintanance, pre-rRNA processing and regulatory activities in alternative splicing. The main role of box C/D snoRNAs is to determine the targets for 2'-O-ribose methylation, which is important for rRNA maturation and splicing regulation of some mRNAs. The targets are still unknown, however, for many 'orphan' snoRNAs. While a fast and efficient target predictor for box H/ACA snoRNAs is available, no comparable tool exists for box C/D snoRNAs, even though they bind to their targets in a much less complex manner. RESULTS: PLEXY is a dynamic programming algorithm that computes thermodynamically optimal interactions of a box C/D snoRNA with a putative target RNA. Implemented as scanner for large input sequences and equipped with filters on the duplex structure, PLEXY is an efficient and reliable tool for the prediction of box C/D snoRNA target sites. AVAILABILITY: The perl script PLEXY is freely available at http://www.bioinf.uni-leipzig.de/Software/PLEXY. Stephanie Kehr, Sebastian Bartschat, Peter F. Stadler, Hakim Tafer |
Bioinform. | 2 |