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Reverberation two-photon microscopy enables video-rate multiplane neuroimaging by performing near-instantaneous axial scanning over large depth ranges while maintaining 3D micrometer-scale resolution.
SMAC-seq combines long-read sequencing with open chromatin methylation by DNA methyltransferases to enable mapping of nucleosome position and chromatin accessibility.
Ubiquitous mammalian enzymes can scavenge uracil analogs, leading to non-specific background in cell-type-specific RNA labeling. This work reveals the enzymes involved and describes the uridine/cytidine kinase 2 and 2′-azidouridine pair as a highly specific and non-toxic alternative.
A statistical method called SPARK for analyzing spatially resolved transcriptomic data can efficiently identify spatially expressed genes with effective control of type I errors and high statistical power.
Advances in MINFLUX nanoscopy enable multicolor imaging over large fields of view, bringing true nanometer-scale fluorescence imaging to labeled structures in fixed and living cells.
Phenotypic earth mover’s distance (PhEMD) facilitates the comparison of single-cell experimental conditions, each of which is a high-dimensional dataset, and identifies axes of variation among multicellular biospecimens.
A template-free image processing approach automatically detects and classifies membrane-bound protein complexes in cryo-electron tomograms of isolated endoplasmic reticulum and in intact cells.
Comprehensive evaluation of algorithms for inferring gene regulatory networks using synthetic and experimental single-cell RNA-seq datasets finds heterogeneous performance and suggests recommendations to users.
Protein–peptide interactions that underpin cell signaling are accurately predicted by wedding the strengths of machine learning with the interpretability of biophysical theory, facilitating detailed mechanistic analyses at the proteome scale.