Demo Data from EDBT 2026 / reviewers in the wild / expert
David C. Baulcombe
dblp:30/10933
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0003-0780-6878ORCID · reported
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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › sequence analysis › RNA sequence analysis
small RNA analysis |
0.1 | 1 | 2012 | Identifying small interfering RNA loci from high-throughput sequencing data · Bioinform. 2012 |
Bioinformatics and computational biology › sequence analysis
high-throughput sequencing data analysis |
0.0 | 1 | 2012 | Identifying small interfering RNA loci from high-throughput sequencing data · Bioinform. 2012 |
Methods — techniques the papers use, named apart from their topics
statistical modeling of replicate information · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Identifying small interfering RNA loci from high-throughput sequencing dataabstractMOTIVATION: Small interfering RNAs (siRNAs) are produced from much longer sequences of double-stranded RNA precursors through cleavage by Dicer or a Dicer-like protein. These small RNAs play a key role in genetic and epigenetic regulation; however, a full understanding of the mechanisms by which they operate depends on the characterization of the precursors from which they are derived. RESULTS: High-throughput sequencing of small RNA populations allows the locations of the double-stranded RNA precursors to be inferred. We have developed methods to analyse small RNA sequencing data from multiple biological sources, taking into account replicate information, to identify robust sets of siRNA precursors. Our methods show good performance on both a set of small RNA sequencing data in Arabidopsis thaliana and simulated datasets. AVAILABILITY: Our methods are available as the Bioconductor (www.bioconductor.org) package segmentSeq (version 1.5.6 and above). Thomas J. Hardcastle, Krystyna A. Kelly, David C. Baulcombe |
Bioinform. | 3 |