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BoxCar, a mass spectrometry data acquisition method, greatly increases sensitivity and the detection of low-abundance peptides with a minimal amount of instrument time.
Several methods make it possible to obtain depth information in 3D super-resolution microscopy. Here the authors exploit a self-interference phenomenon to allow deep imaging within tissue samples, as well as isotropic imaging.
Data-independent-acquisition-based mass spectrometry enables highly reproducible proteome analysis, but results interpretation is challenging owing to the complex nature of the spectral data. A software tool, Specter, effectively resolves spectra for highly similar peptides.
In this CRISPR-based feedback control system, sgRNA expression is triggered by the burden of protein overexpression, and the sgRNA directs repression of the exogenous gene promoter to reduce burdensome expression and restore growth of the cell.
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.
Mime-seq achieves cell-type specific, methylation-based, microRNA tagging and sequencing to uncover cell-specific microRNomes in C. elegans and Drosophila.
Labeling newly transcribed RNA with 5-ethynyluridine and adding biotin via click chemistry allows the analysis of the proteome bound to the various RNA species, including nascent RNA.
Direct sequencing of RNA molecules in real time using nanopores allows for the detection of splice variants and hold promises for profiling RNA modifications.