Scholarlink

<p>Historically, glycomics has lagged behind other omics fields, owing to analytical challenges. However, recent technological advances are rapidly transforming the field, enabling a growing number of large-scale studies to harness the wealth of information encoded by glycans. In this Review, we provide an overview of the current state of large-scale glycomics and its role in understanding the functional importance of glycans. We discuss the main challenges in high-throughput glycoanalytical methods and highlight recent progress, with a particular emphasis on standardization and reproducibility. Special attention is given to the necessity of large, well-designed and ideally longitudinal and multicohort studies that use rigorous statistical approaches to uncover robust biological associations. Finally, we conclude with selected applications and perspectives, emphasizing the potential of large-scale glycomics to drive biomarker discovery and enhance the understanding of glycan-mediated biology.</p><p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Large glycomics datasets as a tool to understand the function of glycans

  • 期刊论文

  • 发表日期：

    2026年5月22日

查看全文
  • Maja Pučić-Baković,
  • Tamara Štambuk,
  • John P. A. Ioannidis,
  • Vlatka Zoldoš,
  • Wei Wang,
  • Gordan Lauc

摘要

Historically, glycomics has lagged behind other omics fields, owing to analytical challenges. However, recent technological advances are rapidly transforming the field, enabling a growing number of large-scale studies to harness the wealth of information encoded by glycans. In this Review, we provide an overview of the current state of large-scale glycomics and its role in understanding the functional importance of glycans. We discuss the main challenges in high-throughput glycoanalytical methods and highlight recent progress, with a particular emphasis on standardization and reproducibility. Special attention is given to the necessity of large, well-designed and ideally longitudinal and multicohort studies that use rigorous statistical approaches to uncover robust biological associations. Finally, we conclude with selected applications and perspectives, emphasizing the potential of large-scale glycomics to drive biomarker discovery and enhance the understanding of glycan-mediated biology.