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This paper presents nonnegative spatial factorization, a general framework for spatially aware and interpretable dimension reduction for high-dimensional spatial data, and its application to spatial transcriptomics analysis.
During the first two years of postnatal development, the human brain undergoes rapid, pronounced changes in size, shape and content. Using high-resolution MRI, we constructed month-to-month atlases of infants 2 weeks to 2 years old, capturing key spatiotemporal traits of early brain development in terms of cortical geometries and tissue properties.
A statistical approach for optimal design of multiplexed imaging studies has been developed. It determines experimental parameters that facilitate cell phenotype identification.
During segmentation of neurons in electron microscopy datasets, auxiliary learning via the prediction of local shape descriptors increases efficiency, which is important for the processing of datasets of ever-increasing size.
We engineered a 3D outer-blood-retina-barrier (3D-oBRB) with a fully polarized retinal pigment epithelium (RPE) monolayer on top of a Bruch’s membrane and a fenestrated choriocapillaris network. This 3D-oBRB tissue faithfully recapitulates RPE– choriocapillaris interactions, dry age-related macular degeneration (AMD) phenotypes (including sub-RPE drusen deposits and choriocapillaris degeneration) and the wet AMD phenotype of choriocapillaris neovascularization.
Antibody-barcode eCLIP (ABC) uses proximity ligation to couple DNA-barcoded antibodies to RNA-binding protein (RBP)-protected RNA fragments for multiplexed eCLIP. ABC can be used to interrogate several RBPs in a single tube with results on par with eCLIP.
This Perspective discusses available software tools for lipidomics data analysis and provides a web-based Lipidomics Tools Guide to help guide the choice of these tools, organized by the major tasks for lipidomics research.
Nano3P-seq presents a nanopore-based sequencing tool to profile polyA-tailed and non-polyA-tailed transcripts, as well as capture polyA tail length and composition.
Localization Model Fit (LocMoFit) is a tool that enables fitting of super-resolution microscopy data to an arbitrary geometric model. The fit extracts quantitative parameters of individual cellular structures, which can be used to investigate dynamic and heterogenous protein assemblies and to create average protein distribution maps.
We trained DEDAL, an algorithm based on deep-learning language models, to generate pairwise alignments of protein sequences taking into account the sequence-specific context of amino acid substitutions or gaps. DEDAL improved the alignment correctness on remote homologs by up to threefold and the discrimination of remote homologs from evolutionarily unrelated sequences.
High-resolution sequencing methods that capture the epigenetic landscape within the T cell receptor (TCR) gene loci are pivotal for a fundamental understanding of the epigenetic regulatory mechanisms of the TCR repertoire. In our opinion, filling the gaps in our understanding of the epigenetic mechanisms regulating the TCR repertoire will benefit the development of strategies that can modulate the TCR repertoire composition by leveraging the dynamic nature of epigenetic modifications.