AIMC Topic: RNA Splicing

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Biogenesis mechanisms of circular RNA can be categorized through feature extraction of a machine learning model.

Bioinformatics (Oxford, England)
MOTIVATION: In recent years, multiple circular RNAs (circRNA) biogenesis mechanisms have been discovered. Although each reported mechanism has been experimentally verified in different circRNAs, no single biogenesis mechanism has been proposed that c...

mirtronDB: a mirtron knowledge base.

Bioinformatics (Oxford, England)
MOTIVATION: Mirtrons arise from short introns with atypical cleavage by using the splicing mechanism. In the current literature, there is no repository centralizing and organizing the data available to the public. To fill this gap, we developed mirtr...

The Splicing Code Goes Deep.

Cell
The importance of genomic sequence context in generating transcriptome diversity through RNA splicing is independently unmasked by two studies in this issue (Jaganathan et al., 2019; Baeza-Centurion et al., 2019).

SpliceRover: interpretable convolutional neural networks for improved splice site prediction.

Bioinformatics (Oxford, England)
MOTIVATION: During the last decade, improvements in high-throughput sequencing have generated a wealth of genomic data. Functionally interpreting these sequences and finding the biological signals that are hallmarks of gene function and regulation is...

Machine learning annotation of human branchpoints.

Bioinformatics (Oxford, England)
MOTIVATION: The branchpoint element is required for the first lariat-forming reaction in splicing. However current catalogues of human branchpoints remain incomplete due to the difficulty in experimentally identifying these splicing elements. To addr...