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Miniature, transparent Danionella fishes, which are among the smallest living adult vertebrates, allow investigation of general principles of brain-wide neural circuits and evolutionary and developmental mechanisms for neurobehavioral innovations.
Single-cell RNA-sequencing and spatial transcriptomics data enable the inference of how information is transmitted from one cell to another and how it modulates gene expression within cells. Now, a learning method infers networks describing how the inflow of one signal, mediated by intracellular gene modules, drives the outflow of other signals for intercellular communication.
FICTURE software addresses a critical challenge in spatial omics analysis: making high-resolution inference with only a few molecules per square micron. This tool fully realizes the potential of contemporary spatial platforms by learning latent spatial factors from the whole transcriptome while preserving the resolution of each technology at scale.
The authors present a workflow integrating imaging mass cytometry and imaging mass spectrometry to deconvolute metabolic heterogeneity at the single-cell level.
Point spread function (PSF) splitting with the ‘Circulator’, which encodes the fluorophore emission band into the PSF, improves the information content of fluorescence microscopy and enables improved super-resolution imaging and single-particle tracking.
Using single-cell and spatial transcriptomics data, FlowSig provides a unified signaling modeling framework by connecting intercellular communication mediated by ligand–receptor interactions and intracellular gene expression modules.
CAST is a deep learning-based method that enables across-sample searching and matching based on spatial molecular features and reconstructing spatially resolved single-cell multi-omic profiles, as well as supports downstream differential analysis.
Spacia is a multiple-instance learning model for cell–cell communication (CCC) interference in single-cell resolution spatially resolved transcriptomics data. Spacia can map complex CCCs by modeling cell proximity and CCC-driven gene perturbation.
FICTURE is a segmentation-free approach for identifying tissue architecture in spatial transcriptomics data. FICTURE is compatible with both imaging-based and sequencing-based methods and is uniquely suited for handling the largest available datasets.
DynaMight models continuous structural heterogeneity in cryo-EM datasets, leading to an improved reconstruction of the consensus structure. The study also explores the issue of overfitting when modeling structural flexibility.
MiLoPYP is a two-step, dataset-specific contrastive learning-based method for fast and accurate detection and localization of a diverse range of target structures in cryo-electron tomography data, enabling improved in situ structural biology.
Combining localization and polarization microscopy can yield detailed insights into subcellular structures. POLCAM uses a polarization camera and wide-field microscopy for rapid measurement of super-resolution orientation imaging in live cells.
Arkitekt is an open-source platform that facilitates the implementation of complex quantitative bioimaging workflows in real time, from acquisition to visualization and analysis.
SN2N, a Self-inspired Noise2Noise module, offers a versatile solution for volumetric time-lapse super-resolution imaging of live cells. SN2N uses self-supervised data generation and self-constrained learning for training with a single noisy frame.
Enhanced Classification of Localized Point clouds by Shape Extraction (ECLiPSE) is a robust feature extraction and classification pipeline for diverse and heterogeneous structures in both 2D and 3D single-molecule localization microscopy data.
WHaloCaMP is a chemigenetic calcium indicator that can be combined with different rhodamine dyes for multiplexed or FLIM imaging in vivo, as demonstrated for calcium imaging in neuronal cultures, brain slices, Drosophila, zebrafish larvae and the mouse brain.
Gapr is an efficient platform for reconstructing neurons in large-scale light microscopy datasets. It enables various proofreading modes as well as collaboration among many annotators.
Collaborative augmented reconstruction (CAR) is a platform for large-scale reconstruction of neurons and other cells from multi-dimensional imaging datasets. It can be accessed from a variety of devices simultaneously for efficient and accurate reconstruction.
The Genomics 2 Proteins portal is an open-source tool for proteome-wide linking of human genetic variants to protein sequences and structures. The portal serves as a discovery tool to hypothesize the structure–function relationship between natural or synthetic variations and their molecular phenotypes.
