EDBT 2026 Demo / reviewers in the wild / expert
Sebastian I Zúñiga Norman
dblp:437/1003
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › gene regulation › gene regulatory network
gene regulatory network analysis |
1.0 | 1 | 2026 | REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research · Bioinform. 2026 |
Bioinformatics and computational biology › single-cell analysis
single-cell RNA sequencing |
1.0 | 1 | 2026 | REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research · Bioinform. 2026 |
Bioinformatics and computational biology
transcriptomics |
1.0 | 1 | 2026 | REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research · Bioinform. 2026 |
Methods — techniques the papers use, named apart from their topics
statistical test · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics ResearchabstractSUMMARY: We introduce REACTOR, a computational tool designed to detect differential activity of transcriptional regulators and their target genes (regulons) in single-cell RNA-sequencing data. It expands the currently available framework for regulon analysis by introducing a robust statistical test to detect differential regulon activity between conditions, such as disease versus control, with multiple replicates. By contrasting different conditions, REACTOR enables identification of key condition- and cell type-specific regulons. To demonstrate the use of REACTOR, we illustrate its performance in a publicly available COVID-19 dataset. AVAILABILITY: REACTOR R-package together with an implementation vignette are available at https://www.github.com/elolab/REACTOR. Markus Lindén, Sebastian I Zúñiga Norman, Tommi Välikangas, Sini Junttila, Tomi Suomi, Kalle T. Rytkönen, Laura Elo |
Bioinform. | 2 |