Structural Landscape of Genetic DiseasesApply
Advances in gene sequencing have led to the production of a wealth of data linking gene mutations to patient phenotypes. Structural biology can often reveal the underlying molecular basis of a particular protein mutation but existing tools only look at one gene at the time. This project aims at producing a software tool that allows performing this structure-function analysis on a large scale and thus to analyze structural mechanisms of diseases from big data resources.
Program - BioScience
Division - Biological and Environmental Sciences and Engineering
Center Affiliation - Computational Bioscience Research Center
Field of Study - Computer science, bioinformatics
Stefan T. Arold
Professor, Bioscience<br/>Associate Dean, Biological and Environmental Science and Engineering Division
Professor Arold’s research interests are focused on integrative structural biology based on hybrid approaches. His work involves inferring structure and function of macromolecular assemblies, to enhance computational methods for functional annotation of genes (system-wide or focused), and to design and engineer molecules with desired properties (switches, genetic/epi-genetic regulators, detectors).
Desired Project Deliverables
Creation of several modules to compute/retrieve sequence-and structure-based properties and integrate them in 3D (structure) space; Conversion and cleanup of high-quality human mutation data from clinical collaborator; Integration and correlation of both.