SiFT reveals hidden biology in single-cell data
In single-cell data analysis, the SiFT methodology stands as a beacon, dedicated to uncovering concealed biological processes. Its innovative approach,…
In single-cell data analysis, the SiFT methodology stands as a beacon, dedicated to uncovering concealed biological processes. Its innovative approach,…
The study of identity-by-descent (IBD) segments in ancient human DNA opens a fascinating window into our ancestral past. Accurate detection…
A study of mitochondrial signaling delves into the role of mitochondria beyond their well-known function in energy metabolism. The researchers…
In protein engineering, achieving stable designs with specific topological structures is a critical pursuit. TPGen, a groundbreaking language model, emerges…
In the pursuit of unraveling DNA methylation biomarkers for various diseases, the selection of an optimal workflow plays a pivotal…
Nutritional intervention with calorie reduction and avoidance of carbohydrates that stimulate excessive insulin demand is a cornerstone of treatment. Physical…
Nascent RNA sequencing run-on experiments play a crucial role in deciphering the dynamic transcriptional landscape of cells. To ensure accurate…
In the realm of single-cell RNA-sequencing (scRNA-seq) data analysis, Cellograph introduces a pioneering semi-supervised approach employing graph neural networks. This…