Web-Based Genomics Tool Designed to Help Predict Disease Susceptibility
PolyDoms database integrates diverse biomedical research information with computational predictions.!--h2>
A new gene information resource designed to aid biomedical researchers in more effectively identifying small alterations in the human genome that are associated with individuals' susceptibility to disease has been established. PolyDoms was developed by researchers at Cincinnati Children's Hospital Medical Center and the University of Cincinnati's Computational Medicine Center.
"PolyDoms is part of a new wave of informatic resources that we and others in the computational biology community are developing to expedite and advance research in personalized, predictive, and preventive medicine," says Bruce Aronow, Ph.D., co-director of the Center for Computational Medicine and professor of pediatrics at Cincinnati Children's and the University of Cincinnati.
PolyDoms offers researchers a single web-based tool that integrates diverse biomedical research information concerning genetic influences of disease with computational predictions of the impact of genomic changes on protein structures and functions. It has a user-friendly graphical and downloadable format that provides researchers with a list of genetic variations that they can analyze in their patient groups to gain more information regarding causes and susceptibility to disease.
"Having this computational tool available to researchers will help prioritize which genetic variations are most likely to alter the structure and function of a protein, and provides us with critical information related to disease susceptibility, progression, and targets for therapeutic interventions," states David A. Schwartz, M.D. director of the National Institute of Environmental Health Sciences (NIEHS), which funded the work along with the NCI.