GRID ENABLED HAP ANALYSIS

该子项目是利用NIH/NCRR资助的中心赠款提供的资源的许多研究子项目之一。子项目和研究者（PI）可能从另一个NIH来源获得主要资金，因此可以在其他CRISP条目中表示。所列机构为中心，不一定是研究者所在机构。本项目旨在开发一种预测非同义单核苷酸多态性（nsSNP）对蛋白质功能影响的技术。该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。该技术涉及在蛋白质的同源物上构建系统发育树，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。该方法已通过将其预测与实验验证的蛋白质突变进行比较来验证。 构建系统发生树和应用概率模型都是计算昂贵的步骤。要建立一个预测所有23，000多个人类基因中所有已知nsSNP影响的数据库，很快就会变得很难。类似地，由于目前并非所有nsSNP都是已知的，因此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.