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Cell2fate improves RNA velocity analysis of single-cell and spatial transcriptomics data by module decomposition of realistic biophysical models of transcription dynamics.
Nellie is a user-friendly tool that streamlines organelle analysis by providing automated segmentation, tracking and feature extraction across any intracellular structure, without the need for deep-learning models or manual parameter adjustment.
Nellie is a comprehensive automated pipeline for studying the structure and intracellular dynamics of diverse organelles that offers accurate segmentation, tracking and feature extraction on both 2D and 3D data.
A first-in-class fluorescence lifetime-based FRET sensor for phosphatase and tensin homolog (PTEN) enables the dynamic monitoring of PTEN activity in cultured cells and in vivo with high spatiotemporal resolution.
Oblique line scan microscopy achieves nanoscale spatial and sub-millisecond temporal resolution across a large field of view, enabling improved and robust single-molecule biophysical measurements and single-molecule tracking in both cells and solution.
The MARBLE method addresses a critical challenge in neural population recordings: inferring expressive and interpretable latent representations that are comparable across experiments and animals. It achieves this by explicitly leveraging the low-dimensional structure of neural states through geometric deep learning to learn the dynamical flow fields in neural activity.
MARBLE uses geometric deep learning to map dynamics such as neural activity into a latent representation, which can then be used to decode the neural activity or compare it across systems.
Segment Anything for Microscopy (μSAM) builds on the vision foundation model Segment Anything for high-quality image segmentation over a wide range of imaging conditions including light and electron microscopy.
Cellpose3 employs deep-learning-based approaches for image restoration to improve cellular segmentation and shows strong generalized performance even on images degraded by noise, blurring or undersampling.
A self-driving multiresolution light-sheet microscope enables the simultaneous observation and quantification of cellular and subcellular dynamics in the context of intact and developing organisms over many hours of imaging.
Building on a nucleosome-depletion strategy, DEFND-seq utilizes a droplet microfluidic platform to enable high-throughput co-profiling of DNA and RNA in single cells.
Proper methods reporting is crucial for transparency, but ensuring method reusability by other labs takes a bit of extra effort. Here we discuss best practices for reporting methods so that they can be reused.
