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Arnaud R. Krebs

dblp:426/1303 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
epigenomics
0.912025
FootprintCharter: unsupervised detection and quantification of footprints in single molecule footprinting data · Bioinform. 2025
Bioinformatics and computational biology › epigenomics › chromatin analysis
nucleosome positioning
0.912025
FootprintCharter: unsupervised detection and quantification of footprints in single molecule footprinting data · Bioinform. 2025

Methods — techniques the papers use, named apart from their topics

unsupervised footprint detection · 0.9motif annotation · 0.9
YearPublicationVenuePosition
2025 FootprintCharter: unsupervised detection and quantification of footprints in single molecule footprinting data
abstract
SUMMARY: Single molecule footprinting profiles the heterogeneity of TF occupancy at cis-regulatory elements across cell populations at unprecedented resolution. The single molecule nature of the data in principle allows for observing the footprint of individual transcription factors and nucleosomes. However, we currently lack algorithms to quantify these occupancy patterns of chromatin binding factors in an automated way and without prior assumptions on their genomic location. Here we present FootprintCharter, an unsupervised tool to detect and quantify footprints for transcription factors (TFs) and nucleosomes from single molecule footprinting data. After detection, TF footprints can be labeled with orthogonal motif annotations provided by the user. FootprintCharter allows for the quantification of complex molecular states such as positioning of unphased nucleosomes and combinatorial co-binding of multiple TFs. AVAILABILITY AND IMPLEMENTATION: FootprintCharter is freely available on Bioconductor with version 2.2.0 of https://bioconductor.org/packages/SingleMoleculeFootprinting through the functions FootprintCharter, PlotFootprints, and Plot_FootprintCharter_SM.
Guido Barzaghi, Arnaud R. Krebs, Judith B. Zaugg
Bioinform.2