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Deep interactome profiling by mass spectrometry (DIP-MS) combines affinity purification with native BN-PAGE fractionation and mass spectrometry to resolve protein complexes sharing the same target protein. The paper also presents PPIprophet, a data-driven neural network-based protein complex deconvolution approach.
RoboEM enables automated proofreading of electron microscopy datasets using a strategy akin to that of self-steering cars. This decreases the need for manual proofreading of segmented datasets and facilitates connectomic analyses.
Improved green cAMP and red calcium sensors were developed to facilitate dual-color imaging in vivo. These sensors will allow studying the relationship between calcium and cAMP signaling.
SpatialData is a user-friendly computational framework for exploring, analyzing, annotating, aligning and storing spatial omics data that can seamlessly handle large multimodal datasets.
scPROTEIN is a deep graph contrastive learning framework that can estimate the uncertainty of peptide quantification, denoise protein data, remove batch effects and encode single-cell proteomic-specific embeddings under a unified framework.
This analysis provides 108 noncoding CRISPR screens collated by the ENCODE4 consortium and establishes experimental guidelines for future CRISPRi screens characterizing functional cis-regulatory elements.
The exceptionally photostable green fluorescent protein StayGold has been monomerized in different laboratories, which has generated three unique monomeric variants that will enable new imaging applications.
New condenser aperture designs form square or rectangular beams that match the camera dimensions, which efficiently expands the data acquisition area in cryogenic electron microscopy.
MINSTED quantifies tiny movements of individual biomolecules with high spatiotemporal precision to successfully resolve the steps of the molecular motor protein kinesin-1 labeled with a single fluorophore as it switches protofilaments.