
Joy W. 2025 | BASIS Independent Fremont
- Project Title: Designing an Algorithmic Framework for Biomarker-Based Disease Detection
With a growing emphasis on non-invasive methods to detect diseases with molecular biomarkers comes a greater demand to find more efficient ways to select primers for singleplex and multiplex assay formulation. While primer selection tools like IDTPrimerQuest and APE alleviate the strain of manually searching for primers, there are numerous requirements for primer selection depending on the disease or target biomarker that these tools do not take into consideration. Further, with the increasing relevance of machine learning in bioinformatics, I hope to explore the potential of applying advanced computing techniques like machine learning and predictive models in primer selection to identify optimal primer pairs, reduce off-target amplification, and adapt to varying or repetitive genomic sequences with greater sensitivity and efficiency.
Hence, the tool I plan on developing would be able to significantly increase the sensitivity of detection tests, as well as decrease resource costs and streamline complex processes to develop non-invasive tests.