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Targeting coalescent analysis (TarCA) is a statistical method that quantifies the number of progenitor cells of a given population using single-cell phylogenetic data.
The authors describe stem cell-derived bone marrow organoids that accurately model the structural and functional properties of the human bone marrow niche.
Vibrational painting (VIBRANT) is a high-content single-cell phenotypic profiling method using mid-infrared imaging with vibrational probes for metabolic activity, which offers high accuracy with minimal batch effects to capture cellular responses to perturbation.
SATURN performs cross-species integration and analysis using both single-cell gene expression and protein representations generated by protein language models.
MEISTER is an integrative experimental and computational framework for mass spectrometry that integrates three-dimensional, organ-wide biomolecular mapping with single-cell analysis for multiscale profiling of spatial–biochemical organization.
Tapioca is an ensemble machine learning framework for studying protein–protein interactions (PPIs) that facilitates integration of curve-based dynamic PPI data from thermal proximity coaggregation, ion-based proteome-integrated solubility alteration or cofractionation mass spectrometry data with static interaction data to predict PPIs in dynamic contexts.
Micro-kiss (μkiss) is a micropipette-based approach for delivering very small amounts of nanoparticles and small molecules to the cell surface with exquisite spatiotemporal control, enabling a wide range of biological investigations.
Transcript Imputation with Spatial Single-cell Uncertainty Estimation (TISSUE) offers a general framework for estimating uncertainty for spatial gene expression predictions, enabling improved downstream analysis of spatially resolved transcriptomics data.
CombFold is a combinatorial and hierarchical assembly algorithm for predicting structures of large protein complexes utilizing pairwise interactions between subunits predicted by AlphaFold2.
ALBATROSS is a deep-learning-based model for predicting ensemble properties of intrinsically disordered proteins and protein regions, such as radius of gyration, end-to-end distance, polymer-scaling exponent and ensemble asphericity, directly from sequences.
RNA family sequence generator (RfamGen) is a deep generative model for designing novel, functional RNA sequences. RfamGen is applicable to diverse RNA families and can yield ribozymes with higher enzymatic activity.
Content-aware frame interpolation (CAFI) improves the temporal resolution in time-lapse imaging by accurately predicting images in between image pairs. By allowing fewer frames to be imaged, CAFI also enables gentler live-cell imaging.
DoTA-seq leverages a microfluidic droplet system to isolate and lyse diverse microbes and amplify target genetic loci, enabling high-throughput single-cell sequencing of microbial populations.
Temporal analysis of relative distances (TARDIS) is a conceptually new alternative to traditional single-particle tracking methods that overcomes challenges associated with high particle density, emitter blinking and spurious localizations.
This work introduces ARTR-seq for in situ measurement of RNA-binding protein (RBP) binding sites, which has been demonstrated in a small number of cells and for capturing dynamic RBP binding within short timeframes.
CytoCommunity enables both supervised and unsupervised analyses of spatial omics data in order to identify complex tissue cellular neighborhoods based on cell phenotypes and spatial distributions.