p53 Disease Variants Classification

Maricel Kann, Department of Biological Sciences
Sai Vallurupalli, Department of Biological Sciences

Functional classification of disease variants is crucial when utilizing precision medicine to improve personalized treatments of patients. Multiple studies have considered molecular links between genes. However, none of them include specific functional effects of gene variants. The purpose of this research is to manually classify variants in genes leading to diseases into gain- or loss-of-function. This will allow for an automatized prioritization of disease-causing genes using network analysis methods that model the gain and loss differently. In order to accomplish this, we will first identify a set of genes of interest that we would like to include in our study. We will then proceed to identify functional keywords that allows us to classify the type of change a variation results in. For instance, if we choose to classify the variants in the oncogene TP53, we will identify the types of variations as either conformational changes or DNA binding changes. Finally, we will classify the specific variants reported in different loci of the genes based on the identified changes in function. This will allow for differential treatments of disease variants with distinct effects, thereby improving prognosis and treatment of diseases.