Methods for profiling RNA and protein expression in a spatially resolved manner are rapidly
evolving, making it possible to comprehensively characterize cells and tissues in health and …

Thanks to innovative sample-preparation and sequencing technologies, gene expression in
individual cells can now be measured for thousands of cells in a single experiment. Since its …

Computational trajectory inference enables the reconstruction of cell state dynamics from
single-cell RNA sequencing experiments. However, trajectory inference requires that the …

The cell type specific sequences of transcriptional programs during lung regeneration have
remained elusive. Using time-series single cell RNA-seq of the bleomycin lung injury model …

Time-series single-cell RNA sequencing (scRNA-seq) datasets provide unprecedented
opportunities to learn dynamic processes of cellular systems. Due to the destructive nature …

Single cell genomics has become a popular approach to uncover the cellular heterogeneity
of progenitor and terminally differentiated cell types with great precision. This approach can …

Deciphering mechanisms of endocrine cell induction, specification and lineage allocation in
vivo will provide valuable insights into how the islets of Langerhans are generated …

Mouse embryonic development is a canonical model system for studying mammalian cell
fate acquisition. Recently, single-cell atlases comprehensively charted embryonic …

Discovering genes with similar functions across diverse biomedical contexts poses a
significant challenge in gene representation learning due to data heterogeneity. In this …

The paradigmatic hematopoietic tree model is increasingly recognized to be limited, as it is
based on heterogeneous populations largely defined by non-homeostatic assays testing cell …