Trained machine-learning models can generate synthetic whole-slide image tiles of tumours from RNA-sequencing data
In cancer research, acquiring diverse and large datasets is often challenging and costly. However, a…
Browsing: Publications
NAP-seq reveals multiple classes of structured noncoding RNAs with regulatory functions
The human genome is a vast landscape of genetic information, but much of it remains…
Single-Cell RNA-seq reveals transcriptomic modulation of Alzheimer’s disease by activated protein C
“We believe our study utilizing Single-Cell RNA sequencing will provide additional rationale towards the effects…
One-pot method for preparing DNA, RNA, and protein for multiomics analysis
Unraveling the complexities of diseases such as cancer often requires a multi-faceted approach, analyzing various…
CLiPPR-Seq – global identification of mRNA-interacting circular RNAs
Circular RNA (circRNA) has garnered considerable attention in recent years due to its regulatory roles…
Artificial spike-ins could improve accuracy of plant RNA-seq analysis
Researchers at NC State have published a simple trick that improves the accuracy of techniques…
Chasing sequencing perfection: marching toward higher accuracy and lower costs
The advent of next-generation sequencing (NGS) technologies has revolutionized the way researchers study genetic information.…
SegPore – raw signal segmentation for estimating RNA modifications and structures from Nanopore direct RNA sequencing data
Estimating RNA modifications from Nanopore direct RNA sequencing data is an important task for the…
ScRAT – phenotype prediction from single-cell RNA-seq data using attention-based neural networks
Understanding the cellular basis of disease phenotypes is crucial for developing targeted therapies. Traditional bulk…
Unveiling reference bias in RNA-seq analysis: implications for complex polyploid genomes
RNA sequencing (RNA-seq) has revolutionized genomics by providing insights into gene expression patterns and regulatory…