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Cells differentiate to their final fates through sequential epigenetic and transcriptional changes. A mathematical model fit on multi-omic single-cell data yields insights into the temporal relationships between chromatin accessibility and gene expression during cell differentiation.
Post-translational modifications (PTMs) alter the structure, properties and functions of proteins in all aspects of biology. A new computational pipeline, termed protein modification integrated search engine (PROMISE), reveals the impact these modifications might have on the presentation of cancer antigens to T cells.
We integrated the pre-characterized physical model of super-resolution (SR) microscopy into a deep neural network to guide the denoising of raw images for high-quality SR image reconstruction. This approach enabled us to investigate a wide variety of fragile and rapidly evolving bioprocesses at ultrahigh spatiotemporal resolution over extended imaging times.