ArticlePloS one2026
TSSpredator-Web: A web-application for transcription start site prediction and exploration.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Deep Generative Model-Driven Design of Microbial Synthetic Promoters.Journal of microbiology and biotechnology · 2025Review
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3 authors.
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Abstract
backgroundWith the rapid development of high-throughput RNA-seq technologies, the transcriptome of prokaryotes can now be studied in unprecedented detail. Transcription start site (TSS) identification provides critical insights into transcriptional regulation. Still, current command-line tools for the prediction of TSS remain challenging with respect to their usability and lack of integrated exploration features.
resultsWe introduce TSSpredator-Web, an interactive web application that enhances the usability of the established yet unpublished tool, TSSpredator. TSSpredator-Web facilitates TSS prediction from non-enriched and enriched RNA-seq data, classifies TSS relative to annotated genes, and allows users to explore results through dynamic visualizations and interactive tables. For the visualizations, we provide an UpSet plot summarizing the TSS distribution across experiments or classes, and a genome viewer that integrates transcriptomic and genomic data, which contextualizes the insights of the TSS predictions. To illustrate the usage of TSSpredator-Web, we provide a use case with Cappable-seq data from Escherichia coli. TSSpredator-Web is available on the TueVis visualization web-server at https://tsspredator-tuevis.cs.uni-tuebingen.de/.
conclusionsBy combining user-friendly accessibility with interactive data exploration, TSSpredator-Web significantly facilitates genome-wide TSS analysis and interpretation in prokaryotes, empowering a broader range of researchers to generate biological insights from transcriptomic data.
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