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By effective and efficient integration of PacBio HiFi, Oxford Nanopore Technologies ultra-long and other sequencing data types, hifiasm (UL) enables telomere-to-telomere diploid and polyploid genome assembly at a population scale.
We developed a two-pronged strategy to functionally probe the enormous repertoire of noncoding DNA within genomes. Our approach markedly improved signal-to-noise ratio and successfully intersected single-cell genomics with reporter assays. The result delivers a multiplex and highly quantitative readout of regulatory sequences’ activity in dynamic and multicellular systems.
By learning to embed DNA k-mers and cells into a joint space, CellSpace improves single-cell ATAC-seq analysis in multiple tasks such as latent structure discovery, transcription factor activity inference and batch effect mitigation.
Single-cell quantitative expression reporters enable high-sensitivity quantitative characterization of cis-regulatory elements at the single-cell level in multicellular systems.
Molecular Pixelation is an optics-free method that uses DNA-tagged antibodies to enable identification of the relative location of proteins on single cells.
Combining post-translational modification site-centric base editing with phenotypic screens uncovers the function of phosphorylation sites in high throughput, enabling the study of expansive signaling networks at a speed comparable to that of functional genomics.
Combining genome-wide CRISPR–Cas9-mediated base editors with temporally resolved phosphoproteomics enables the functional screening of thousands of post-translational modification sites involved in T cell activation.
ESI-cryoPrep is a cryo-EM specimen preparation method that employs electrospray ionization techniques to deposit charged macromolecule-containing droplets on EM grids. Demonstrated across various protein samples, this approach effectively prevents biomolecule adsorption at air–water or graphene–water interfaces, addressing challenges related to protein denaturation and preferred orientation.
Super-resolution imaging of reference and target structures enables precise determination of the labeling efficiency of high-affinity binding proteins in cells for improved quantitative assessment of protein organization at the single-molecule level.
To those who seek transcriptomic information at high resolution, scale and throughput, single-cell RNA sequencing brings the data. Scientists share tips and future plans as they reflect on the method’s rise to stardom.
This Perspective discusses the potential of protein structure-prediction models for exploring the structural landscape and specificity of TCR–pMHC interactions.
We created DELiVR, a deep-learning pipeline for 3D brain-cell mapping that is trained with virtual reality-generated reference annotations. It can be deployed via the user-friendly interface of the open-source software Fiji, which makes the analysis of large-scale 3D brain images widely accessible to scientists without computational expertise.
Generating training data for training deep-learning-based tools is time consuming. The DELiVR pipeline facilitates this process as demonstrated in this study on detecting c-Fos+ cells or microglia in the brain, following tissue clearing and imaging with light-sheet microscopy.