AIMC Topic: Alternative Splicing

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DIFFUSE: predicting isoform functions from sequences and expression profiles via deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Alternative splicing generates multiple isoforms from a single gene, greatly increasing the functional diversity of a genome. Although gene functions have been well studied, little is known about the specific functions of isoforms, making...

PathwaySplice: an R package for unbiased pathway analysis of alternative splicing in RNA-Seq data.

Bioinformatics (Oxford, England)
SUMMARY: Pathway analysis of alternative splicing would be biased without accounting for the different number of exons or junctions associated with each gene, because genes with higher number of exons or junctions are more likely to be included in th...

COSSMO: predicting competitive alternative splice site selection using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Alternative splice site selection is inherently competitive and the probability of a given splice site to be used also depends on the strength of neighboring sites. Here, we present a new model named the competitive splice site model (COS...

Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision.

Nucleic acids research
Alternative splicing (AS) is a genetically and epigenetically regulated pre-mRNA processing to increase transcriptome and proteome diversity. Comprehensively decoding these regulatory mechanisms holds promise in getting deeper insights into a variety...

Complementary feature selection from alternative splicing events and gene expression for phenotype prediction.

Bioinformatics (Oxford, England)
MOTIVATION: A central task of bioinformatics is to develop sensitive and specific means of providing medical prognoses from biomarker patterns. Common methods to predict phenotypes in RNA-Seq datasets utilize machine learning algorithms trained via g...