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Phage and robotics-assisted near-continuous evolution enables phage-assisted continuous evolution in high throughput, allowing for improved exploration of sequence space and insight into how variables affect evolution outcomes.
3D-CASH is a random-access microscopy approach that avoids in vivo motion artifacts by sampling each targeted neuron with a holographically shaped grid of illumination spots. The technology allows recording neuronal activity in the mouse cortex at a throughput of 20,000 neurons per second.
HaloTag variants offer distinct brightness and fluorescence lifetimes compared with HaloTag7 when labeled with rhodamines. These variants were used for multiplexed imaging with a single fluorophore and to create lifetime-based cell cycle indicators.
mBrainAligner is a cross-modal registration platform for whole mouse brains imaged with different modalities. In addition, a fluorescence micro-optical sectioning tomography-based mouse brain atlas has been generated.
This manuscript proposes the use of spectral entropy similarity as a measure of similarity for small-molecule mass spectra and the use of a one-bond-difference approach for improving false discovery rates.
Anterograde transneuronal tracing can be achieved with engineered variants of the yellow fever vaccine YFV-17D. Both monosynaptic and polysynaptic tracing are demonstrated in different circuits of the mouse brain.
This work presents biotin-DNA affinity purification (DAP) sequencing, that is, an in vitro, clone-free workflow to profile transcription factor (TF) DNA binding, as well as multiDAP to simultaneously characterize TF DNA binding in multiple bacterial genomes.
pGlyco3 is a glycan-first glycopeptide search engine for the identification and localization of site-specific N- and O-glycopeptides, including glycopeptides with modified glycans.
Hierarchical phase-contrast tomography (HiP-CT) enables multiscale imaging of any region within an intact human organ down to cellular resolution. HiP-CT of five organ types revealed 3D morphological features in healthy and diseased tissue.
HERMES is a molecular-formula-oriented and peak-detection-free method that uses LC/MS1 information to optimize MS2 acquisition for LC/MS-based metabolomic analysis.
The Signac framework enables the end-to-end analysis of single-cell chromatin data and interoperability with the Seurat package for multimodal analysis.
SpaGCN is a spatially resolved transcriptomics data analysis tool for identifying spatial domains and spatially variable genes using graph convolutional networks.
The NetID algorithm annotates untargeted LC-MS metabolomics data by combining known biochemical and metabolomic principles with a global network optimization strategy.
DeepLC, a deep learning-based peptide retention time predictor, can predict retention times for unmodified peptides as well as peptides with previously unseen modifications.