TripLexicon: prediction and analysis of gene regulatory RNA-DNA interactions

1 December 2025·
Dr. Timothy Warwick
Christina Wrobel (formerly Kalk)
Christina Wrobel (formerly Kalk)
,
Ralf P. Brandes
,
Marcel H. Schulz
· 0 min read
DOI
Abstract
MOTIVATION: Non-coding RNA (ncRNA) plays a crucial role in gene regulation, including by forming sequence-specific RNA-DNA interactions at gene regulatory elements. One form of interaction takes place via the formation of RNA:DNA:DNA triple helices (triplexes). Accurate computational prediction of triplex formation from nucleotide sequences is an important tool in ncRNA research but remains somewhat inaccessible and complex. To address this, we created TripLexicon, a web-based interface for accessing and analyzing predicted gene regulatory RNA-DNA interactions in human and mouse. RESULTS: Predicted interactions can be accessed from RNA-, DNA-, and region-centric perspectives. For each RNA transcript, visualizations at genome and nucleotide resolution are available, providing insight into target genes and regions, as well as putative functional domains of the transcript. Predicted target genes can immediately be subjected to ontology and pathway enrichment analysis, providing rapid insight into potential functions mediated by the RNA-DNA interactions of the queried transcript. DNA and region queries are designed to identify potentially important ncRNA interactors at sites of interest. AVAILABILITY AND IMPLEMENTATION: TripLexicon is accessible at https://triplexicon.uni-frankfurt.de. This website is free and open to all users and there is no login requirement. All data and code is uploaded to Zenodo: https://zenodo.org/records/17143608 and the code for the webserver is available on Github: https://github.com/SchulzLab/TripLexicon.
Type
Publication
Bioinformatics (Oxford, England)
publications
Authors
Senior AI Research Scientist
Alex Johnson is a Senior AI Research Scientist at Meta AI. His research has been published in top conferences like NeurIPS and ICML, with over 10,000 citations. Alex is passionate about pushing the boundaries of AI while ensuring ethical development.
Christina Wrobel (formerly Kalk)
Authors
PhD student
A Biochemist by training, I developed a strong interest in data analysis and statistics which led me to pursue a second Master’s degree in Statistics and Data Science. During this time, I also joined the lab as a PhD student. Since then I worked on diverse projects at the intersection of computational biology, bioinformatics and RNA research. My research mainly focuses on RNA translation regulation, aiming to uncover the mechanisms that control protein production in cells and how these processes differ across cell types, conditions, and disease states.