Unraveling cell–cell communication with NicheNet by inferring active ligands from transcriptomics data
Ligand–receptor interactions constitute a fundamental mechanism of cell–cell communication and signaling. NicheNet is a well-established comput…
Ligand–receptor interactions constitute a fundamental mechanism of cell–cell communication and signaling. NicheNet is a well-established comput…
Teravoxel-scale, cellular-resolution images of cleared rodent brains acquired with light-sheet fluorescence microscopy have transformed the way we …
A key challenge of the modern genomics era is developing empirical data-driven representations of gene function. Here we present the first unbiased…
Advances in computational structure prediction will vastly augment the hundreds of thousands of currently available protein complex structures. Tra…
Neuroimaging has entered the era of big data. However, the advancement of preprocessing pipelines falls behind the rapid expansion of data volume, …
Accurate segmentation of objects in microscopy images remains a bottleneck for many researchers despite the number of tools developed for this purp…
The dynamics of neuron populations commonly evolve on low-dimensional manifolds. Thus, we need methods that learn the dynamical processes over neur…
Cellular organelles undergo constant morphological changes and dynamic interactions that are fundamental to cell homeostasis, stress responses and …
RNA velocity exploits the temporal information contained in spliced and unspliced RNA counts to infer transcriptional dynamics. Existing velocity m…