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Distance distribution correction (DDC) eliminates repeat localizations caused by fluorophore blinking without the need for calibrations. Use of DDC yields accurate and quantifiable single-molecule localization microscopy data.
Combining whole-transcriptome preindexing with standard droplet microfluidics, scifi-RNA-seq enables single-cell RNA-seq with massive throughput and built-in sample multiplexing.
Surveying targets by APOBEC-mediated profiling identifies binding sites of RBPs by C-to-U RNA editing. STAMP is isoform specific, can be multiplexed and enables detection of ribosome association in single cells.
A deep learning–based algorithm enables efficient reconstruction of light-field microscopy data at video rate. In addition, concurrently acquired light-sheet microscopy data provide ground truth data for training, validation and refinement of the algorithm.
This paper reports CoTECH, which couples chromatin binding enrichment with RNA sequencing for concurrent measurements of histone modification and transcriptome in single cells, offering a multiomics tool for studying epigenetic regulations.
The CEPT cocktail comprising four small molecules enhances pluripotent stem cell survival, biobanking, organoid formation, and single-cell cloning efficiency by reducing cellular stress.
This work describes the identification of Cas13 proteins from two families by mining public metagenomic data. The newly identified Cas13X.1 shows efficient target knockdown and can be used to degrade SARS-CoV-2 and H1N1 genomes. In addition, the truncated Cas13X.1 offers an advantage in generating mini-RNA base editors.
DANNCE enables robust 3D tracking of animals’ limbs and other features in naturalistic environments by making use of a deep learning approach that incorporates geometric reasoning. DANNCE is demonstrated on behavioral sequences from rodents, marmosets, and chickadees.
PCprophet combines complex-level scoring and machine learning to predict novel protein complexes from protein cofractionation mass spectrometry data and to perform differential analysis across experimental conditions.
Phasor S-FLIM combines novel electronics for multichannel fluorescence lifetime acquisition and a phasor-based unmixing algorithm for real-time analysis of reliable spectral lifetime imaging data, enabling new biological observations.
A deep-learning-guided approach enables protein engineering using only a small number (‘low N’) of functionally characterized variants of target proteins.
This work describes nanodisco, a tool for de novo identifying DNA methylation in bacterial species and microbiomes using nanopore sequencing and for performing metagenomic binning using microbial DNA methylation patterns.
Martini 3.0 is an updated and reparametrized force field for coarse-grained molecular dynamics simulations with new bead types and an expanded ability to model molecular packing and interactions.
A suite of generally applicable methods and tools, developed to enable single-molecule FRET-based studies of transmembrane proteins diffusing in the cell membrane of living cells, was used to study the oligomerization and dynamics of GPCRs.
Point-scanning super-resolution imaging uses deep learning to supersample undersampled images and enable time-lapse imaging of subcellular events. An accompanying ‘crappifier’ rapidly generates quality training data for robust performance.
Advances in single-cell sequencing technologies enable generation of datasets of millions of cells. scfind facilitates efficient and sophisticated gene search in massive single-cell datasets.
HD-fMOST is a microscopy technique for imaging large samples at high throughput and with high definition, which is achieved with a line-illumination modulation approach. The technology is illustrated by imaging fluorescently labeled neurons in whole mouse brains.
This work reports a dual transposase–peroxidase fusion to survey the accessible chromatin regions and the proximal proteome in one assay, providing a tool to capture both the genomic and proteomic contents of open chromatin.