Next generation tools for the annotation of human SNPs
Next generation tools for the annotation of human SNPs
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DOI：
10.1093/bib/bbn047
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发表时间：
2009-01-01
影响因子：
9.5
通讯作者：
Karchin, Rachel
中科院分区：
文献类型：
--
作者：
Karchin, Rachel
计算生物学有机会在鉴定大规模基因分型研究中发现的功能性单核苷酸多态(SNPs)方面发挥重要作用，最终产生新的药物靶点和生物标记物。医学遗传学和分子生物学社区越来越多地转向计算生物学方法，以优先处理在连锁和关联研究中发现的有趣的SNP。许多这样的方法现在都可以通过网络界面获得，但感兴趣的用户面临着一系列经常相互不一致的预测结果。今天的许多工具产生的结果如果没有生物信息学专业知识就很难理解，偏向于非同义的SNP，并且不一定反映其源生物信息学资源的最新版本，例如公共SNP存储库。在这里，我将评估当前一代网络服务器的效用，并为下一代网络服务器提出改进建议，以便更好地为医学遗传学家和分子生物学家提供价值。
Computational biology has the opportunity to play an important role in the identification of functional single nucleotide polymorphisms (SNPs) discovered in large-scale genotyping studies, ultimately yielding new drug targets and biomarkers. The medical genetics and molecular biology communities are increasingly turning to computational biology methods to prioritize interesting SNPs found in linkage and association studies. Many such methods are now available through web interfaces, but the interested user is confronted with an array of predictive results that are often in disagreement with each other. Many tools today produce results that are difficult to understand without bioinformatics expertise, are biased towards non-synonymous SNPs, and do not necessarily reflect up-to-date versions of their source bioinformatics resources, such as public SNP repositories. Here, I assess the utility of the current generation of webservers; and suggest improvements for the next generation of webservers to better deliver value to medical geneticists and molecular biologists.