VLDB 2026 Research / reviewers in the wild / expert
Robert M. Miura
dblp:36/4045
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2006
—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 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › gene regulation
cis-regulatory element analysis |
0.1 | 1 | 2006 | Prediction of mRNA polyadenylation sites by support vector machine · Bioinform. 2006 |
Bioinformatics and computational biology › RNA biology › RNA processing
polyadenylation site prediction |
0.1 | 1 | 2006 | Prediction of mRNA polyadenylation sites by support vector machine · Bioinform. 2006 |
Methods — techniques the papers use, named apart from their topics
support vector machine · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | Prediction of mRNA polyadenylation sites by support vector machineabstractmRNA polyadenylation is responsible for the 3' end formation of most mRNAs in eukaryotic cells and is linked to termination of transcription. Prediction of mRNA polyadenylation sites [poly(A) sites] can help identify genes, define gene boundaries, and elucidate regulatory mechanisms. Current methods for poly(A) site prediction achieve moderate sensitivity and specificity. Here, we present a method using support vector machine for poly(A) site prediction. Using 15 cis-regulatory elements that are over-represented in various regions surrounding poly(A) sites, this method achieves higher sensitivity and similar specificity when compared with polyadq, a common tool for poly(A) site prediction. In addition, we found that while the polyadenylation signal AAUAAA and U-rich elements are primary determinants for poly(A) site prediction, other elements contribute to both sensitivity and specificity of the prediction, indicating a combinatorial mechanism involving multiple elements when choosing poly(A) sites in human cells. Robert M. Miura, Bin Tian 0002 |
Bioinform. | 2 |