BMC Bioinformatics. 2014;15 Suppl 1(Suppl 1):S9. doi: 10.1186/1471-2105-15-S1-S9. Epub 2014 Jan 10.
Recent progress in method development for characterising the branched structures of complex carbohydrates has now enabled higher throughput technology. Automation of structure analysis then calls for software development since adding meaning to large data collections in reasonable time requires corresponding bioinformatics methods and tools. Current glycobioinformatics resources do cover information on the structure and function of glycans, their interaction with proteins or their enzymatic synthesis. However, this information is partial, scattered and often difficult to find to for non-glycobiologists.
Following our diagnosis of the causes of the slow development of glycobioinformatics, we review the "objective" difficulties encountered in defining adequate formats for representing complex entities and developing efficient analysis software.
Various solutions already implemented and strategies defined to bridge glycobiology with different fields and integrate the heterogeneous glyco-related information are presented.
Despite the initial stage of our integrative efforts, this paper highlights the rapid expansion of glycomics, the validity of existing resources and the bright future of glycobioinformatics.
最近在开发用于描述复杂碳水化合物支链结构的方法方面取得了进展,现在已经能够实现更高的通量技术。由于要在合理的时间内为大量数据集合赋予意义,需要相应的生物信息学方法和工具,因此结构分析的自动化需要软件开发。当前的糖生物信息学资源确实涵盖了聚糖的结构和功能、它们与蛋白质的相互作用或它们的酶合成信息。然而,这些信息是局部的、分散的,对于非糖生物学家来说往往难以找到。
在我们诊断出糖生物信息学发展缓慢的原因后,我们回顾了在定义表示复杂实体的适当格式和开发高效分析软件方面遇到的“客观”困难。
提出了已经实现的各种解决方案和定义的策略,以弥合糖生物学与不同领域的差距,并整合异构的糖相关信息。
尽管我们的综合工作处于初始阶段,但本文强调了糖组学的快速发展、现有资源的有效性以及糖生物信息学的光明未来。