miRNACNET

Overview

miRNAs are clinically relevant cancer biomarkers that have proven applications in machine learning-based cancer detection systems. However, the relationship between the relevance of the top miRNAs used by machine learning models and the performance metrics of those models has not yet been fully explored. Further exploration will better connect machine learning approaches with clinical approaches to cancer detection.

Community Benefit

The research paper furthered the state of knowledge regarding the clinical and biological relevance of the miRNAs used by machine learning models for cancer classification and the relationship between relevance and classification performance. The PCA also revealed distinct patterns of miRNA dysregulation across tissues. The web application deployed the models used in developing the experiments in a user-friendly environment. The application represents a method for deploying machine learning based clinical applications in a way that is useful for practitioners.

Team Members

• Matthew Acs - macs2019@fau.edu 
• Richard Acs - racs2019@fau.edu 
• Charles Briandi - cbriandi2019@fau.edu 
• Eyan Eubanks - eeubanks2019@fau.edu 
• Matthew Stewart - stewartm2018@fau.edu 

Sponsor

Dr. Hanqi Zhuang