sc-linker – identifying disease-critical cell types and cellular processes by integrating single-cell RNA-sequencing and human genetic
Genome-wide association studies provide a powerful means of identifying loci and genes contributing to disease,…
Browsing: Publications
Spatial total RNA-sequencing shows role of elusive RNA in muscle regeneration
In recent years, scientists who study gene expression in cells have used a method that…
Unique molecular identifiers and multiplexing amplicons maximize the utility of deep sequencing to critically assess population diversity in RNA viruses
Next generation sequencing (NGS)/deep sequencing has become an important tool in the study of viruses.…
Single-molecule counting method for digital quantification of SARS-CoV-2 RNA
Digital counting individual nucleic acid molecule is of great significance for fundamental biological research and…
Researchers have created a catalog of RNA editing sites in the brain
Mount Sinai researchers have catalogued thousands of sites in the brain where RNA is modified…
FusionSeeker – gene fusion detection and characterization in long-read cancer transcriptome sequencing data
Gene fusions are prevalent in a wide array of cancer types with different frequencies. Long-read…
RNA-sensing system measures and controls protein expression in cells
A new technology called RADARS allows scientists to detect and target specific cell types, opening…
Biological misinterpretation of transcriptional signatures can undermine faithful alignment between clinical samples and preclinical data/models
Precise mechanism-based gene expression signatures (GES) have been developed in appropriate in vitro and in…
Single-cell RNA-sequencing reveals pathways for aggressive prostate cancer subtype
Cribriform prostate cancer is an aggressive subtype of the disease characterized by its histology, but…
A comparison of whole genome and whole transcriptome sequencing reveals phenotypic variation in cancer cells often not due to mutations
From The Scientist by Jef Akst Most models of how tumors evolve have assumed that…