David C. Gemperline

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Autophagic turnover of intracellular constituents is critical for cellular housekeeping, nutrient recycling, and various aspects of growth and development in eukaryotes. Here we show that autophagy impacts the other major degradative route involving the ubiquitin-proteasome system by eliminating 26S proteasomes, a process we termed proteaphagy. Using(More)
We analyse sequence and structural features of protein-RNA interfaces using RB-147, a non-redundant dataset of protein-RNA complexes extracted from the PDB. We train classifiers using machine learning algorithms to predict protein-RNA interfaces from sequence and structure-derived features of proteins. Our experiments show that Struct-NB, a Naive Bayes(More)
We explore whether protein-RNA interfaces differ from non-interfaces in terms of their structural features and whether structural features vary according to the type of the bound RNA (e.g., mRNA, siRNA...etc.), using a non-redundant dataset of 147 protein chains extracted from protein-RNA complexes in the protein data bank. Our analysis of surface(More)
Label-free quantitative MS based on the Normalized Spectral Abundance Factor (NSAF) has emerged as a straightforward and robust method to determine the relative abundance of individual proteins within complex mixtures. Here, we present Morpheus Spectral Counter (MSpC) as the first computational tool that directly calculates NSAF values from output obtained(More)
The 26S proteasome is a highly dynamic, multisubunit, ATP-dependent protease that plays a central role in cellular housekeeping and many aspects of plant growth and development by degrading aberrant polypeptides and key cellular regulators that are first modified by ubiquitin. Although the 26S proteasome was originally enriched from plants over 30 years(More)
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