Demo Data from EDBT 2026 / reviewers in the wild / expert
Viktor Tokan
dblp:327/9395
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved
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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › epigenomics
3d genome organization |
0.6 | 1 | 2022 | HiC-TE: a computational pipeline for Hi-C data analysis to study the role of repeat family interactions in the genome 3D organization · Bioinform. 2022 |
Bioinformatics and computational biology › epigenomics
hi-c data analysis |
0.6 | 1 | 2022 | HiC-TE: a computational pipeline for Hi-C data analysis to study the role of repeat family interactions in the genome 3D organization · Bioinform. 2022 |
Methods — techniques the papers use, named apart from their topics
nextflow pipeline · 0.6heatmap visualization · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | HiC-TE: a computational pipeline for Hi-C data analysis to study the role of repeat family interactions in the genome 3D organizationabstractMOTIVATION: The role of repetitive DNA in the 3D organization of the interphase nucleus is a subject of intensive study. In studies of 3D nucleus organization, mutual contacts of various loci can be identified by Hi-C sequencing. Typical analyses use binning of read pairs by location to reduce noise. We use binning by repeat families instead to make similar conclusions about repeat regions. RESULTS: To achieve this, we combined Hi-C data, reference genome data and tools for repeat analysis into a Nextflow pipeline identifying and quantifying the contacts of specific repeat families. As an output, our pipeline produces heatmaps showing contact frequency and circular diagrams visualizing repeat contact localization. Using our pipeline with tomato data, we revealed the preferential homotypic interactions of ribosomal DNA, centromeric satellites and some LTR retrotransposon families and, as expected, little contact between organellar and nuclear DNA elements. While the pipeline can be applied to any eukaryotic genome, results in plants provide better coverage, since the built-in TE-greedy-nester software only detects tandems and LTR retrotransposons. Other repeats can be fed via GFF3 files. This pipeline represents a novel and reproducible way to analyze the role of repetitive elements in the 3D organization of genomes. AVAILABILITY AND IMPLEMENTATION: https://gitlab.fi.muni.cz/lexa/hic-te/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Matej Lexa, Monika Cechova, Son Hoang Nguyen, Pavel Jedlicka, Viktor Tokan, Zdenek Kubat, Roman Hobza, Eduard Kejnovský |
Bioinform. | 5 |