The input of the DeepTXsolver is the parameters of the mechanism model, and the output is the corresponding stationary distribution solution of the model. The input to the DeepTXinferrer is the ...

To infer gene regulatory networks (GRNs) of mixed populations in scRNA-seq data, the research team utilized the mixture ...

Single-cell sequencing applications have accelerated breakthroughs in life sciences, leading to significant impacts for disease treatments. Single-nuclei RNA-sequencing (snRNA-Seq) has been shown to ...

Single cell RNA sequencing (scRNA-seq) provides the resolution and scale to unravel the complexity of cancer biology and reveal insights to advance human health. Join Dr. Allison Stewart and Dr. Carl ...

A recent study has unraveled the intricate cellular blueprint behind the iconic fragrance of Prunus mume flowers.

RNA-Seq allows the quantification of gene expression levels ... The integration of NGS with other technologies, such as single-cell sequencing, spatial transcriptomics, and multi-omics approaches, ...

"RNA sequencing (RNA-seq) is a powerful technique that allows scientists to analyze the quantity and variety of RNA in a sample. This helps researchers understand gene expression and how it affects ...

By Dr. Sushama R. Chaphalkar, PhD. A deep-learning method creates a comprehensive reference atlas of CD8+ T cells, ...

"RNA sequencing (RNA-seq) is a powerful technique that allows scientists to analyze the quantity and variety of RNA in a sample. This helps researchers understand gene expression and how it ...