Publications by authors named "Keith C Cheveralls"
Article Synopsis
- Understanding how proteins are localized in cells is key to grasping cellular structure and function.
- The new tool, Cytoself, uses deep learning and self-supervised training to create a detailed map of protein localization without needing prior data or labels.
- Cytoself has been shown to effectively group proteins into organelles and complexes, outperforming previous methods, and the study also analyzes the features and components that contribute to its success.
Article Synopsis
- The study aims to map out how human cells are organized by using a combination of advanced techniques involving genome engineering, imaging, and data analysis.
- Researchers identified specific protein localization patterns that help reveal molecular interactions and functional communities within the cell.
- Their findings, along with an interactive website, provide valuable tools for understanding the complex networks that govern cellular organization.
The mechanism responsible for the accurate partitioning of newly replicated Escherichia coli chromosomes into daughter cells remains a mystery. In this article, we use automated cell cycle imaging to quantitatively analyse the cell cycle dynamics of the origin of replication (oriC) in hundreds of cells. We exploit the natural stochastic fluctuations of the chromosome structure to map both the spatial and temporal dependence of the motional bias segregating the chromosomes.
View Article and Find Full Text PDFThe stochasticity of chromosome organization was investigated by fluorescently labeling genetic loci in live Escherichia coli cells. In spite of the common assumption that the chromosome is well modeled by an unstructured polymer, measurements of the locus distributions reveal that the E. coli chromosome is precisely organized into a nucleoid filament with a linear order.
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