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PRICE uses Ribo-seq data to predict ORFs and start codons with high accuracy by computationally eliminating experimental noise and dissecting overlapping translation events.
cellAlign enables quantitative comparisons of expression dynamics within and between single-cell trajectories based on single-cell RNA-seq or mass cytometry data.
Embedding a deep-learning model in the known structure of cellular systems yields DCell, a ‘visible’ neural network that can be used to mechanistically interpret genotype–phenotype relationships.
The combination of photoactivatable fluorescent markers with single-cell RNA-seq allows transcriptome analysis of cells from specific tissue locations.