ArticleBioinformatics advances2025
Exonize: a tool for finding and classifying exon duplications in annotated genomes.
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Summary: The protein-coding regions of eukaryotic genes are fragmented into exons that, like the genes within which they are situated, can be duplicated, deleted, or reorganized. Cataloging and organizing within-gene exon similarities is necessary for a systematic study of exon evolution and its consequences. To facilitate the study of exon duplications, we present Exonize, a computational tool that identifies and classifies coding exon duplications in annotated genomes. Exonize implements a graph-based framework to handle clusters of related exons resulting from repeated rounds of exon duplication. The interdependence between duplicated exons or groups of exons across transcripts is classified. By identifying duplication events between exonic and intronic regions, Exonize can detect unannotated or degenerate exons. To aid in data parsing and downstream analysis, the Python module exonize_analysis is provided. The application of Exonize to 20 eukaryote genomes identifies full-exon duplications in at least 4% of vertebrate genes, with more than 900 human genes having a full-exon duplication event. Availability and implementation: Exonize is available at https://github.com/msarrias/exonize.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.