GRID ENABLED HAP ANALYSIS

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 该项目旨在开发一种预测非同义单核苷酸多态(NsSNP)对蛋白质功能影响的技术。这个项目可以为那些将基因与他们感兴趣的疾病联系起来的医学研究人员提供重要的见解。这项技术包括在蛋白质的同源物上建立系统发育树，然后应用概率模型来确定nsSNP是否会对蛋白质产生有害影响。通过将其预测与实验验证的蛋白质突变进行比较，该方法得到了验证。 构建系统发育树和应用概率模型都是计算昂贵的步骤。为所有23,000多个人类基因中所有已知的nsSNPs的影响建立一个预测数据库很快就变得困难起来。同样，由于目前并不是所有的nsSNPs都是已知的，预测数据库需要不断更新。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This project aims to develop a technique for predicting the effect of a non-synonymous single nucleotide polymorphism (nsSNP) on the function of a protein. This project can provide important insights to medical researchers who have linked a gene to their disease of interest. This technique involves building a phylogenetic tree over homologues of the protein and then applying a probabilistic model to determine whether or not the nsSNP will have a deleterious effect on the protein. This method has been verified by comparing its predictions to experimentally verified protein mutations. Building a phylogenetic tree and applying the probabilistic model are both computationally expensive steps. It quickly becomes intractable to make a database of predictions for the effect of all known nsSNPs in all 23,000+ human genes. Similarly, since not all nsSNPs are currently known, the database of predictions needs to constantly be updated.