Nature Methods, Published online: 25 July 2024; doi:10.1038/s41592-024-02365-9biVI models the biophysical processes generating nascent and mature single-cell transcriptomes using variational autoencoders.

Nature Methods, Published online: 22 July 2024; doi:10.1038/s41592-024-02341-3PINNACLE is a context-specific geometric deep learning model for generating protein representations. Leveraging single-cell transcriptomics combined with networks of protein–protein interactions, cell type-to-cell type interactions and a tissue hierarchy, PINNACLE generates...

Nature Methods, Published online: 22 July 2024; doi:10.1038/s41592-024-02349-9Bayesian nonparametric Track (BNP-Track) simultaneously determines emitter numbers and their tracks alongside uncertainty, extending the superresolution paradigm from static samples to single-particle tracking even in dense environments.

Nature Methods, Published online: 22 July 2024; doi:10.1038/s41592-024-02342-2We developed PINNACLE, a graph-based AI model for learning protein representations across cell-type contexts. These contextualized protein representations enable the integration of 3D protein structure with single-cell genomic-based representations to enhance protein–protein...

Nature Methods, Published online: 18 July 2024; doi:10.1038/s41592-024-02360-0EpiChem enables the co-profiling of small molecule–DNA interactions and multiple epigenomic features in single cells.

Nature Methods, Published online: 18 July 2024; doi:10.1038/s41592-024-02340-4cryoDRGN-ET is a generative neural network method for heterogeneous reconstruction of cryo-ET subtomograms. Using subtomogram tilt-series images, it can capture states diverse in both composition and conformation.