Theoretical studies focusing on the nature of landscapes that correlate molecular sequences to molecular function have mainly been carried out in silico due to the vast amounts of data that are needed for analysis. In vitro selections of aptamers are a good model system to study theoretical questions at a experimental level. With the introduction of robotic platforms that conduct in vitro selections, it is now capable of producing significant amounts of data in a short time, making theoretical modeling with real experimental data attainable.

I will be using a Biomek 2000 Laboratory Automation Workstation to carry out multiple in vitro nucleic acid selections in parallel. I will explore the sequence space to examine whether existing in vitro selection systems are optimal at isolating the best winning species. New methods will be introduced that will allow for the selection of identical targets with identical pools free of cross contamination on the open robotic system. This will open the doors to further conduct selections against other identical or highly similar targets, such as complex cellular targets.

Finally, I will investigate the methods to improve the effectiveness at isolating aptamers against the highly complex lung cancer cell lines. These targets are highly challenging for isolating specific aptamers because of the great diversity of biomarkers found among them. Moreover, their highly morphological similarity of the cultured cells makes selections for specific aptamers very difficult. I explore the different methods that will allow for the generation of aptamers that can distinguish between non-small cell lung cancer and small cell lung cancer, and between non-small cell lung cancer and normal lung cells. Fine-tuning of this process is essential at transferring this process to automated platforms for large-scale generation of biosensors against tumor biomarkers.