Cells are essential to understanding health and disease, yet traditional models fall short of
modeling and simulating their function and behavior. Advances in AI and omics offer …

Since the discovery of RNA splicing and its role in gene expression, researchers have
sought a set of rules, an algorithm or a computational model that could predict the splice …

Most mammalian genes have multiple polyA sites, representing a substantial source of
transcript diversity regulated by the cleavage and polyadenylation (CPA) machinery. To …

A systematic evaluation of how model architectures and training strategies impact genomics
model performance is needed. To address this gap, we held a DREAM Challenge where …

The exponential growth of big data in RNA biology (RB) has led to the development of deep
learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL …

Alternative splicing plays a crucial role in protein diversity and gene expression regulation in
higher eukaryotes, and mutations causing dysregulated splicing underlie a range of genetic …

Alternative splicing is crucial for cancer progression and can be targeted pharmacologically,
yet identifying driver exons genome-wide remains challenging. We propose identifying such …

The branchpoint (BP) motif is an essential intronic element for spliceosomal pre-mRNA
splicing. In mammals, its sequence composition, distance to the downstream exon, and …

Ribonucleic acid (RNA) plays a variety of crucial roles in fundamental biological processes.
Recently, RNA has become an interesting drug target, emphasizing the need to improve our …

Abstract Vision-Language Pretraining (VLP) and Foundation models have been the go-to
recipe for achieving SoTA performance on general benchmarks. However, leveraging these …