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Daniel Wolozny

Researcher at Johns Hopkins University

Publications -  6
Citations -  311

Daniel Wolozny is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Proteome & Chinese hamster ovary cell. The author has an hindex of 5, co-authored 6 publications receiving 274 citations.

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Proteomic Analysis of Chinese Hamster Ovary Cells

TL;DR: This first large-scale proteomic analysis of Chinese hamster ovary (CHO) cells will enhance the knowledge base about CHO capabilities for recombinant expression and provide information useful in cell engineering efforts aimed at modifying CHO cellular functions.
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Physiologic and pathophysiologic consequences of altered sialylation and glycosylation on ion channel function

TL;DR: An overview of sialic acids, potassium and sodium channel function, and the impact of sIALylation on channel activation and deactivation is provided.
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The non-apoptotic action of Bcl-xL: regulating Ca(2+) signaling and bioenergetics at the ER-mitochondrion interface.

TL;DR: The MAM is a critical cell-signaling junction whereby Bcl-xL dynamically interacts with IP3R3 to coordinate mitochondrial Ca2+ transfer and alters cellular metabolism in order to increase the cells’ bioenergetic capacity, particularly during periods of stress.
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Elucidation of the CHO Super-Ome (CHO-SO) by Proteoinformatics.

TL;DR: A publically accessible web-based tool called GO-CHO is created to functionally categorize proteins found in CHO-SO and identify enriched molecular functions, biological processes, and cellular components that will enable the CHO community to rapidly identify high-abundance HCPs in cultures and therefore help assess process and purification methods used in the production of biologic drugs.
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Glycoproteomic and glycomic databases

TL;DR: This study reviews 15 different publicly available databases of glycosylation related databases and identifies their key elements so that users can identify the most applicable platform for their analytical needs to characterize and categorize glycoproteins and glycans better for biomedical research.