ArticleFrontiers in molecular biosciences2021
GeneTrail: A Framework for the Analysis of High-Throughput Profiles.
Article in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- A scoping review of approaches to evaluating workflow management systems for bioinformatics users.Briefings in bioinformatics · 2026Article
- Transcriptional profiling of male mouse muscle across aging stages: a gene ontology analysis of the muscle matreotype.BMC genomics · 2026Article
- vissE.cloud: a webserver to visualise higher order molecular phenotypes from enrichment analysis.Nucleic acids research · 2023Article
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Authors and funding
10 authors.
Funding
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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.
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Registered trials
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