Please use this identifier to cite or link to this item: doi:10.22028/D291-46241
Title: GeneTrail: A Framework for the Analysis of High-Throughput Profiles
Author(s): Gerstner, Nico
Kehl, Tim
Lenhof, Kerstin
Eckhart, Lea
Schneider, Lara
Stöckel, Daniel
Backes, Christina
Meese, Eckart
Keller, Andreas
Lenhof, Hans-Peter
Language: English
Title: Frontiers in Molecular Biosciences
Volume: 8
Publisher/Platform: Frontiers
Year of Publication: 2021
Free key words: COVID-19
enrichment analysis
gene regulation
web server
time-serie analysis
single-cell analysis
network analyis
gene set analysis
DDC notations: 004 Computer science, internet
610 Medicine and health
Publikation type: Journal Article
Abstract: Experimental high-throughput techniques, like next-generation sequencing or microarrays, are nowadays routinely applied to create detailed molecular profiles of cells. In general, these platforms generate high-dimensional and noisy data sets. For their analysis, powerful bioinformatics tools are required to gain novel insights into the biological processes under investigation. Here, we present an overview of the GeneTrail tool suite that offers rich functionality for the analysis and visualization of (epi-)genomic, transcriptomic, miRNomic, and proteomic profiles. Our framework enables the analysis of standard bulk, time-series, and single-cell measurements and includes various state-of-the-art methods to identify potentially deregulated biological processes and to detect driving factors within those deregulated processes. We highlight the capabilities of our web service with an analysis of a single-cell COVID-19 data set that demonstrates its potential for uncovering complex molecular mechanisms. GeneTrail can be accessed freely and without login requirements at http://genetrail.bioinf.uni-sb.de.
DOI of the first publication: 10.3389/fmolb.2021.716544
URL of the first publication: https://doi.org/10.3389/fmolb.2021.716544
Link to this record: urn:nbn:de:bsz:291--ds-462416
hdl:20.500.11880/40533
http://dx.doi.org/10.22028/D291-46241
ISSN: 2296-889X
Date of registration: 10-Sep-2025
Description of the related object: Supplementary Material
Related object: https://www.frontiersin.org/articles/10.3389/fmolb.2021.716544/full#supplementary-material
Faculty: M - Medizinische Fakultät
MI - Fakultät für Mathematik und Informatik
Department: M - Humangenetik
M - Medizinische Biometrie, Epidemiologie und medizinische Informatik
MI - Informatik
Professorship: M - Univ.-Prof. Dr. Andreas Keller
M - Prof. Dr. Eckart Meese
MI - Prof. Dr. Hans-Peter Lenhof
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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