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  • We 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 interaction prediction, analysis of drug effects across cell-type contexts, and prediction of therapeutic targets in a cell type-specific manner.

    Research Briefing
  • PINNACLE 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 high-resolution protein representations tailored to each cell type.

    • Michelle M. Li
    • Yepeng Huang
    • Marinka Zitnik
    ArticleOpen Access
  • Bayesian 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.

    • Ioannis Sgouralis
    • Lance W. Q. Xu
    • Steve Pressé
    ArticleOpen Access
  • Onavg is a surface template of the human cortex. In contrast to existing templates, the cortical surface is uniformly sampled, which has advantages in numerous applications.

    • Ma Feilong
    • Guo Jiahui
    • James V. Haxby
    ArticleOpen Access
  • SwitchSeeker combines computational and experimental techniques to identify functional RNA structural switches. Applied to the human transcriptome, it identified a novel RNA switch in the 3ʹUTR of RORC, linked to nonsense-mediated decay.

    • Matvei Khoroshkin
    • Daniel Asarnow
    • Hani Goodarzi
    ArticleOpen Access
  • Bats, the only flying mammals, comprise almost 25% of mammalian species. They are excellent navigators, highly social, and extremely long-lived. Their sense of echolocation has been studied for many years — but many species possess also excellent vision and olfaction. In recent years, bats have emerged as new models for neurobiology of navigation, social neuroscience, aging, and immunity.

    • Liora Las
    • Nachum Ulanovsky
    This Month
  • Tissues and organs are inherently three-dimensional. Studies to understand their function and dysfunction should therefore aim to maintain the 3D spatial context.

  • Machine learning approaches can distinguish six different classes of presynapses from electron micrographs across the Drosophila brain.

    • Rita Strack
    Research Highlight
  • Keypoint-MoSeq is an unsupervised behavior segmentation algorithm that extracts behavioral modules from keypoint tracking data acquired with diverse algorithms, as demonstrated in mice, rats and fruit flies. The extracted modules faithfully reflect human-annotated behaviors even though they are obtained in an unsupervised fashion.

    • Caleb Weinreb
    • Jonah E. Pearl
    • Sandeep Robert Datta
    ArticleOpen Access
  • This Perspective discusses the methods and tools required for three-dimensional histology in large samples, an approach that promises insights into tissue and organ physiology as well as disease.

    • Ali Ertürk
  • SpatialGlue is a tool designed to decipher spatial domains from spatial multi-omics data acquired from a single tissue section. It employes graph neural networks with a dual-attention mechanism to accomplish within-omics integration of measured features and spatial information, followed by cross-omics integration.

    Research Briefing
  • We demonstrate CRISPRdelight, a robust CRISPR–Cas12a-based method for imaging non-repetitive genomic DNAs in a highly efficient way. This system is a powerful tool for studying functional links between gene dynamics, localization and regulation, and reveals heterogeneity in the expression of differently localized alleles in the same cells.

    Research Briefing