Demo Data from SIGIR 2026 / reviewers in the wild / expert
Dominika Labudová
dblp:276/0819
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2020
—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 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 bioinformatics › RNA structure prediction
g-quadruplex prediction |
0.4 | 1 | 2020 | pqsfinder web: G-quadruplex prediction using optimized pqsfinder algorithm · Bioinform. 2020 |
Bioinformatics and computational biology › structural bioinformatics › molecular structure prediction
nucleic acid structure prediction |
0.4 | 1 | 2020 | pqsfinder web: G-quadruplex prediction using optimized pqsfinder algorithm · Bioinform. 2020 |
Methods — techniques the papers use, named apart from their topics
recursive algorithm · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | pqsfinder web: G-quadruplex prediction using optimized pqsfinder algorithmabstractMOTIVATION: G-quadruplex is a DNA or RNA form in which four guanine-rich regions are held together by base pairing between guanine nucleotides in coordination with potassium ions. G-quadruplexes are increasingly seen as a biologically important component of genomes. Their detection in vivo is problematic; however, sequencing and spectrometric techniques exist for their in vitro detection. We previously devised the pqsfinder algorithm for PQS identification, implemented it in C++ and published as an R/Bioconductor package. We looked for ways to optimize pqsfinder for faster and user-friendly sequence analysis. RESULTS: We identified two weak points where pqsfinder could be optimized. We modified the internals of the recursive algorithm to avoid matching and scoring many sub-optimal PQS conformations that are later discarded. To accommodate the needs of a broader range of users, we created a website for submission of sequence analysis jobs that does not require knowledge of R to use pqsfinder. AVAILABILITY AND IMPLEMENTATION: https://pqsfinder.fi.muni.cz, https://bioconductor.org/packages/pqsfinder. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Dominika Labudová, Jirí Hon, Matej Lexa |
Bioinform. | 1 |