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<h1> Large-scale approaches for glycobiology </h1> <p> <em>Christopher T Campbell<sup>1</sup> and Kevin J Yarema<sup>1</sup></em> </p> <div> <em></em> <div> <em><sup>1</sup>Department of Biomedical Engineering, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218, USA</em> </div> </div> <div> <em>Corresponding author.</em> </div> <p> <em><span style="white-space:nowrap;">Kevin J Yarema: <span><a href="mailto:kyarema1@jhu.edu">kyarema1@jhu.edu</a></span></span></em> </p> <div> <em><span>Genome Biol. </span><span>2005; </span><span>6</span><span>(11)</span><span>: 236. </span></em> </div> <p> </p> <h3> Abstract </h3> <div style="text-transform:none;"> </div> <div> Glycosylation, the attachment of carbohydrates to proteins and lipids, influences many biological processes. Despite detailed characterization of the cellular components that carry out glycosylation, a complete picture of a cell's glycoconjugates remains elusive because of the challenges inherent in characterizing complex carbohydrates. This article reviews large-scale techniques for accelerating progress in glycobiology. </div> <p> </p>
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