GRID ENABLED HAP ANALYSIS

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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.