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Hormonal Pathways and Trait Expression Simulator

Live Project

Overview

This project is an interactive simulation tool designed to help researchers and students explore the dynamic relationship between hormone sensitivity and reproductive fitness in male songbirds. By manipulating key parameters like hormone concentrations and tissue sensitivity, users can visualize the impact of these factors on reproductive success over time.

Research Context

The simulator is based on the dynamic state variable model developed by Dr. Nicole Baran, Ph.D., in behavioral neuroendocrinology. The model provides insights into how hormone receptor sensitivity, rather than just hormone concentration, plays a critical role in influencing various traits related to reproductive fitness. This forward-looking model aims to optimize fitness at each reproductive cycle by adjusting hormone sensitivity across different tissues.

Features

1. Graphical Visualizations

• Interactive Sliders: Control hormone concentration, tissue sensitivity, and other variables through easy-to-use sliders.
• Multi-Run Simulations: Compare how varying specific inputs across multiple runs affects reproductive outcomes.
• Statistics & Model Insights: Generate visual and statistical outputs to deepen your understanding of the hormone-receptor interaction model.

2. Tissue-Level Simulation

• User-Controlled Inputs: Explore how hormone receptor counts and hormone concentration influence trait expression in male songbirds.
• Dynamic Legends & Buttons: Toggle between visualizations and legends that clarify the behavior of the model.

3. Environmental Simulation

• Interactive Traits Visualization: View how a bird’s ability to regulate hormone sensitivity affects multiple traits, including reproductive behaviors, across breeding cycles.

Next Steps

• AI Integration: Add AI-generated explanations for model outputs to enhance usability for diverse audiences.
• Mobile Compatibility: Improve accessibility features for mobile devices.
• Reproductive Cycles: Incorporate full reproductive cycles to better link tissue sensitivity to reproductive outcomes.
• User Testing: Conduct testing with target audiences to refine the user experience.
• Publishing: Collaborate with Dr. Baran to publish the simulator alongside her research.

Tech Stack

• Frontend: Svelte
• Backend: Flask, Python
• Mathematical Modeling: MATLAB

Software Developers

• Karisma Lavana
• William McCune III
• Brandon Rivera
• Haruta Otaki
• Nelson Anderson
• Vanessa Lin

Acknowledgments

We extend our gratitude to:

• Dr. Nicole Baran, Faculty at Davidson College
• Aaron Kutnick, Team Lead
• Dr. Heyer, Stakeholder
• NCShare Project Sponsors and Code+ Directors

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