Back

Non3nExonFinder: transcript-aware identification of shared non-triplet coding exons

Lee, S.-Y.; Lee, J.-H.

2026-09-28 bioinformatics
10.64898/2026.09.22.753378 bioRxiv
Show abstract

Selection of an appropriate coding exon is an important upstream step in exon deletion-based loss-of-function strategies, particularly for genes with multiple transcript isoforms. However, manual comparison of exon structures across multiple transcripts can be time-consuming and may overlook transcript-specific differences in exon boundaries and coding sequence (CDS) composition. Non3nExonFinder was developed as an interactive R/Shiny-based tool for identifying shared non-triplet coding exons across user-defined human or mouse NCBI RefSeq protein-coding transcripts. Non3nExonFinder evaluates exon/CDS annotations and coding contributions for each transcript, identifies common exons with identical genomic boundaries, and prioritizes candidates based on CDS-only status and coding-length divisibility by three. Non-triplet CDS-only exons that are internal in all selected transcripts are classified as high-confidence candidates. Independent reconstruction from the original RefSeq GTF files across 80 genes (40 human and 40 mouse), comprising 6,848 transcript-specific exon instances, showed complete concordance with Non3nExonFinder outputs, with exact recovery of all candidate sets. Non3nExonFinder provides a reproducible upstream framework for transcript-aware prioritization of exon-deletion targets.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.