fairfolio
Saved Projects

Dopavision: A Novel Supervised Machine Learning Model for Predicting Post-Cocaine Phasic Mesolimbic Dopamine Activity in Male C57BL/6J Mice

ISEF · 2025 Computational Biology and Bioinformatics

Yoon, Sumin · Collierville High School

Overview

Dysregulated dopamine in the mesolimbic system is linked to disorders like schizophrenia, depression, and addiction. Low phasic dopamine release correlates with reduced drug reward sensitivity and reduced motivation, but no reliable method exists to predict phasic dopamine levels. This study developed a prototype machine learning model, Dopavision, to predict percent changes in phasic dopamine release following common behavioral testing in mice. Using social and locomotor data, the multiple linear regression explained 60.18% of dopamine variability, while the random forest classifier algorithm achieved 83.33% accuracy. Future research can refine the model for both sexes, potentially enabling human DA prediction and early disorder prevention.

Competition history

Resources

Related projects

Closest projects by meaning, across every fair and year in the corpus.

Browse more like this

Source: Regeneron International Science and Engineering Fair

Save projects to your library

Sign in with Google to keep track of projects you find interesting, organized into folders. An account also raises your daily allowance for “Has this been done?”, and lets you create a key for the MCP server with a much higher limit than anonymous use. Browsing stays public.

Continue with Google