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As one of the most extensive and important protein post-translational modifications, glycosylation plays a vital role in regulating organisms and is associated with various physiological and pathological processes. Recently, researchers have focused on the need to characterize protein glycosylation sites, structures, and their degree of modification, to better understand their biological functions while also looking for potential biomarkers for diagnosis and treatment of disease.
Mass spectrometry (MS) is one of the most powerful tools used to study biomolecules including glycoproteins and glycans. With the continuous development of glycoproteomics and glycomics based on MS analysis, more techniques have evolved and contribute to understanding the structure and function of glycoproteins and glycans. This book reviews advancements achieved in MS-based glycoproteomic analysis, including a wide range of analytical methodologies and strategies involved in selective enrichment; as well as qualitative, quantitative, and data analysis, together with their clinical applications. Significant examples are discussed to illustrate the principles, laboratory protocols, and advice for key implementation to ensure successful results.
Mass Spectrometry–Based Glycoproteomics and Its Clinic Application will serve as a valuable resource to elucidate new techniques and their applications for students, postdocs, and researchers working in proteomics, glycoscience, analytical chemistry, biochemistry, and clinical medicine.
Editor:
Haojie Lu is a professor at Fudan University, specializing in proteomics based on mass spectrometry with particular emphasis on novel technologies for separation and identification of low-abundant proteins and post-translationally modified proteins (including glycosylation), as well as relative and absolute quantification methods for proteomics.
Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
Memmo's summaries are gold before exams. I don't have to re-read 800 pages two weeks before — just the important parts.
The AI chat has saved me the night before an exam more than once. I just keep asking until I get it — no waiting on a study group to reply.
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The AI podcasts are my favorite. I listen on my way to school and get a recap without sitting at a computer.
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