Most human genes have multiple sites at which RNA 3ʹ end cleavage and polyadenylation
can occur, enabling the expression of distinct transcript isoforms under different conditions …

Deep learning, which is especially formidable in handling big data, has achieved great
success in various fields, including bioinformatics. With the advances of the big data era in …

Alternative polyadenylation (APA) is a major driver of transcriptome diversity in human cells.
Here, we use deep learning to predict APA from DNA sequence alone. We trained our …

Gene regulation is a central topic in cell biology. Advances in omics technologies and the
accumulation of omics data have provided better opportunities for gene regulation studies …

Background 3′-end processing by cleavage and polyadenylation is an important and finely
tuned regulatory process during mRNA maturation. Numerous genetic variants are known to …

We review the current applications of artificial intelligence (AI) in functional genomics. The
recent explosion of AI follows the remarkable achievements made possible by “deep …

Sequence-based machine learning models trained on genome-scale biochemical assays
improve our ability to interpret genetic variants by providing functional predictions describing …

The tremendous amount of biological sequence data available, combined with the recent
methodological breakthrough in deep learning in domains such as computer vision or …

Motivation Messenger RNA subcellular localization mechanisms play a crucial role in post-
transcriptional gene regulation. This trafficking is mediated by trans-acting RNA-binding …

Alternative polyadenylation (APA) plays important roles in modulating mRNA stability,
translation, and subcellular localization, and contributes extensively to shaping eukaryotic …