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 ...

Single Cell Clustering Assessment Framework (SCCAF) is a novel method for automated identification of putative cell types from single cell RNA-seq (scRNA-seq) data. By iteratively applying clustering ...

Dynamic interactions between brain regions, either during rest or performance of cognitive tasks, have been studied extensively using a wide variance of methods. Although some of these methods allow ...

Region-specific patterns of neural activity are present at birth in rodents and are thought to refine synaptic connections during critical periods of cerebral cortex development. Marsupials are born ...

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CStreet uses time-series information to construct the k-nearest neighbors connections within and between time points. Then, CStreet calculates the connection probabilities of cell states and ...

In order to define if the modules identified in the variability network are functionally relevant, we performed a Gene Ontology (GO) enrichment analysis. We find that some of the modules have strongly ...

Many physiological processes are driven by changes across heterogeneous populations of cells. However, we currently lack a conceptual framework for comparing single-cell transcriptional data collected ...