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Intrinsically disordered regions of proteins are prevalent across the kingdoms of life; however, biophysical characterization is expensive, requiring specialized expertise and equipment and time-consuming sample preparation. By combining simulations and deep learning, we have developed a method to predict their average ensemble properties directly from sequence.
ALBATROSS is a deep-learning-based model for predicting ensemble properties of intrinsically disordered proteins and protein regions, such as radius of gyration, end-to-end distance, polymer-scaling exponent and ensemble asphericity, directly from sequences.
Improvements to the fully genetically encoded Neonothopanusnambi bioluminescence pathway enhance autobioluminescence by up to two orders of magnitude in plants and other species, enabling novel applications of bioluminescence imaging in biology.
A square electron beam improves imaging of large fields of view in transmission electron microscopes by facilitating montage tomography of vitrified specimens with no loss in data quality relative to conventional round beams.
RNA family sequence generator (RfamGen) is a deep generative model for designing novel, functional RNA sequences. RfamGen is applicable to diverse RNA families and can yield ribozymes with higher enzymatic activity.
Content-aware frame interpolation (CAFI) improves the temporal resolution in time-lapse imaging by accurately predicting images in between image pairs. By allowing fewer frames to be imaged, CAFI also enables gentler live-cell imaging.
DoTA-seq leverages a microfluidic droplet system to isolate and lyse diverse microbes and amplify target genetic loci, enabling high-throughput single-cell sequencing of microbial populations.
Temporal analysis of relative distances (TARDIS) is a conceptually new alternative to traditional single-particle tracking methods that overcomes challenges associated with high particle density, emitter blinking and spurious localizations.
ARTR-seq uses antibody-guided in situ reverse transcription to efficiently and accurately identify RNA-binding protein target sites in as few as 20 cells, or in a formaldehyde-fixed tissue section. The high temporal resolution of ARTR-seq opens opportunities for the investigation of dynamic RNA-binding protein–RNA interactions.
This work introduces ARTR-seq for in situ measurement of RNA-binding protein (RBP) binding sites, which has been demonstrated in a small number of cells and for capturing dynamic RBP binding within short timeframes.
Neurodesk is a platform for analyzing human neuroimaging data, which provides numerous tools in a containerized form, thereby ensuring reproducibility and portability.