Demo Data from EDBT 2026 / reviewers in the wild / expert
Luyao Ruan
dblp:197/8198
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—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 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › RNA biology › RNA analysis
RNA structure probing |
0.3 | 1 | 2017 | SEQualyzer: interactive tool for quality control and exploratory analysis of high-throughput RNA structural profiling data · Bioinform. 2017 |
Bioinformatics and computational biology › genomics
high-throughput sequencing data |
0.1 | 1 | 2017 | SEQualyzer: interactive tool for quality control and exploratory analysis of high-throughput RNA structural profiling data · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
statistical quality metrics · 0.3interactive visualization · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | SEQualyzer: interactive tool for quality control and exploratory analysis of high-throughput RNA structural profiling dataabstractSummary: To serve numerous functional roles, RNA must fold into specific structures. Determining these structures is thus of paramount importance. The recent advent of high-throughput sequencing-based structure profiling experiments has provided important insights into RNA structure and widened the scope of RNA studies. However, as a broad range of approaches continues to emerge, a universal framework is needed to quantitatively ensure consistent and high-quality data. We present SEQualyzer, a visual and interactive application that makes it easy and efficient to gauge data quality, screen for transcripts with high-quality information and identify discordant replicates in structure profiling experiments. Our methods rely on features common to a wide range of protocols and can serve as standards for quality control and analyses. Availability and Implementation: SEQualyzer is written in R, is platform-independent, and is freely available at http://bme.ucdavis.edu/aviranlab/SEQualyzer. Contact: [email protected] Supplementary Informantion: Supplementary data are available at Bioinformatics online. Krishna Choudhary, Luyao Ruan, Nathan P. Shih, Sharon Aviran |
Bioinform. | 2 |