Databases

A recent study aggregated RNA sequencing data from more than 3000 samples to create a user-friendly database of transcription profiles in...

With advanced technologies to map RNA modifications, our understanding of them has been revolutionized, and they are seen to be far more widespread and important than previously thought...

The development of single cell RNA-sequencing (scRNA-seq) technologies has greatly contributed to deciphering the tumor microenvironment (TME). An enormous amount of independent scRNA-seq studies have been published representing a valuable resource that provides opportunities for meta-analysis studies. However, the massive ...

Alternative splicing (AS) is a post-transcriptional regulation that leads to the complexity of the transcriptome. Despite the growing importance of...

Transcribed RNAs undergo various regulation and modification to become functional transcripts. Notably, cancer transcriptome has not been fully characterized at transcript resolution. Researchers at the Shanghai Jiao Tong University School of Medicine carried out a reference-based transcript assembly across >1000 ...

Microbial communities are massively resident in the human body, yet dysbiosis has been reported to correlate with many diseases, including various...

Livestock animals is of great significance in agricultural production. However, the role of specific gene expression, especially alternative splicing in determining phenotype, is not well understood...

Non-coding RNAs (ncRNAs) play important roles in regulating expression of protein-coding genes. Although gene expression databases have emerged in a timely manner, a comprehensive expression...

RNA G-quadruplexes (RG4s) are non-canonical, disease-associated post-transcriptional regulators of gene expression whose functions are driven by RNA-binding proteins (RBPs). Being able to explore transcriptome-wide RG4 formation and interaction with RBPs is thus paramount to understanding how they are regulated and ...

Single-cell RNA-sequencing (scRNA-seq) is one of the most used single-cell omics in recent decades. The exponential growth of single-cell data has...