The winning methods for predicting cellular position in the DREAM single-cell transcriptomics challenge

August 26, 2020 Leave a comment 2,865 Views

Predicting cell locations is important since with the understanding of cell locations, we may estimate the function of cells and their integration with the spatial environment. Thus, the DREAM challenge on single-cell transcriptomics required participants to predict the locations of ...

RNA-Seq Blog Transcriptome Research & Industry News

Tag Archives: cellular position prediction

The winning methods for predicting cellular position in the DREAM single-cell transcriptomics challenge

Learning to predict RNA sequence expressions from whole slide images

CRIC-seq – global profiling of in-situ RNA–RNA contacts associated with a specific RNA-binding protein

Novel machine-learning algorithm creates atlas of cancer with potential as universal diagnostic platform

Long noncoding RNA profiling may be effective for stratification in pediatric AML

spSeudoMap – cell type mapping of spatial transcriptomics using unmatched single-cell RNA-seq data

SoCube – an innovative end-to-end doublet detection algorithm for analyzing scRNA-seq data

Quantabio adds powerful bead booster chemistry to ultra-fast sparQ RNA-Seq HMR kit