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Skani enables accurate and efficient genome comparison for modern metagenomic datasets
Modern high-throughput metagenomics is producing hundreds of thousands of metagenome-assembled genomes (MAGs), which is overwhelming traditional sequence-similarity search methods. We present a computational method, skani, that efficiently compares MAGs on a terabyte scale while being robust to the inherent noise in MAGs, enabling larger and more accurate analyses.
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Method of the Year 2021: Protein structure prediction
Protein structure prediction is our Method of the Year 2021, for the remarkable levels of accuracy achieved by deep learning-based methods in predicting the 3D structures of proteins and protein complexes, essentially solving this long-standing challenge.
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Community-developed checklists for publishing images and image analyses
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Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells
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GelMap: intrinsic calibration and deformation mapping for expansion microscopy
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Statistically unbiased prediction enables accurate denoising of voltage imaging data