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 …

Drug resistance is perhaps the greatest obstacle in improving outcomes for cancer patients,
leading to recurrence, progression and metastasis of various cancers. Exploring the …

Functional studies of long noncoding RNAs (lncRNAs) have been hindered by the lack of
methods to assess their evolution. Here we present lncRNA Homology Explorer (lncHOME) …

As a pivotal post-transcriptional modification of RNA, N6-methyladenosine (m6A) has a
substantial influence on gene expression modulation and cellular fate determination …

During oocyte maturation and early embryogenesis, changes in mRNA poly (A)-tail lengths
strongly influence translation, but how these tail-length changes are orchestrated has been …

Neurodegenerative diseases are commonly classified as proteinopathies that are defined by
the aggregation of a specific protein. Parkinson's disease (PD) and dementia with Lewy …

Understanding the mechanisms of pre-mRNA splicing is limited by the technical challenges
to examining spliceosomes in vivo. Here, we report the isolation of RNP complexes derived …

Developing quantitative models of substrate specificity for RNA processing enzymes is a key
step toward understanding their biology and guiding applications in biotechnology and …

Without new transcription, gene expression across the oocyte-to-embryo transition (OET)
relies instead on regulation of mRNA poly (A) tails to control translation. However, how tail …

Sequence-specific RNA-binding proteins (RBPs) play central roles in splicing decisions.
Here, we describe a modular splicing architecture that leverages in vitro-derived RNA affinity …