Single-cell RNA-seq AI analysis has become the default way to make sense of the millions of expression measurements a single experiment can now generate. Turning raw sequencing counts into ...

A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...

In the past decade there has been significant interest in studying the expression of our genetic code down to the level of single cells, to identify the functions and activities of any cell through ...

Celldetective is an open-source software integrating segmentation, tracking, and event detection to perform high-throughput end-to-end study of dynamic cell interactions, without requiring coding ...

Essentially all cells in an organism's body have the same genetic blueprint, or genome, but the set of genes that are actively expressed at any given time in a cell determines what type of cell it ...

Multiomics data integration with machine learning has become the standard approach for combining genomic, transcriptomic, proteomic, and metabolomic measurements collected from the same biological ...

Researchers headed by a team at the University of California, Irvine, Joe C. Wen School of Population & Public Health have built what they suggest is the first cell type-specific gene regulatory ...

Announcing a new article publication in BIO Integration. The authors of this article developed CellDeathAnalysis (v0.4.0), an ...