Optimization of Optical Signal in Microarrays: Predicting properties of polycrystalline ZnO coatings

This project addresses an important need for more reliable diagnostics and health care testing. DNA microarray technology coupled with PCR has enabled a dramatic improvement in high]throughput clinical diagnostics, with analogous advances from other biomolecular and chemical microarrays in areas of metabolomics, proteomics, etc. There is still room for improvement, however, in boosting signal from low]replicate samples and reducing false positives from either fluorescence noise or lower fidelity hybridization or coupling. Our work can address these problems and enhance signal by developing new coatings for DNA microarray chips which will allow for detection of lower signals, increased reproducibility, and elimination of background signal and false positives. The first stage (this project) involves computational modeling to pre]screen and identify the most promising coating or set of coatings. Within a year we would have evidence to proceed with fabrication of the candidate coatings, for testing in prototype devices.

Faculty Supervisor:

Erika Merschrod

Student:

Csaba Szakacs

Partner:

Atlantic Computational Excellence Network (ACEnet) and NewLab Life Sciences Inc.

Discipline:

Chemistry

Sector:

Nanotechnologies

University:

Memorial University of Newfoundland