Pilot City Project Minigames

Pilot City Project Minigames

This is an adventure game with numerous interactions to simulate and address real-life concerns in the field of Biotechnology. Moreover, this game highlights the numerous achievements that the Scripps Research Institute has accomplished.

Game Hub Frontend & Backend Repositories

Game Hub Links

KanBan Board

Next Plan

Final Plan

Ideate

The Scripps Research: Biotech Engagement Game Development project uses interactive games to introduce students to biotechnology. Each game is built around real scientific data and machine learning models, allowing players to tackle challenges like predicting disease outbreaks or designing new treatments. Through gameplay, students experience how data and AI are used in real-world research to solve major health problems.

What is its purpose?

This project makes biotechnology education more engaging and accessible. Many students struggle with biotech concepts through traditional learning, but this project turns them into interactive experiences. By using real-world datasets and machine learning models, players analyze data, make decisions, and see real-time outcomes. This hands-on approach builds problem-solving skills and a deeper understanding of how biotech research impacts global health. Beyond education, the project addresses real-world challenges like disease outbreaks, genetic engineering, and drug discovery. By immersing students in these scenarios, it highlights the role of biotechnology in solving critical health issues.

Source

The main source of the project itself is the Scripps Research Institute, however, we will be using a variety of datasets to simulate real-life conditions that prompt critical thinking skills. We will be using the adventure game from Mr. Mort’s website as a base for all our work.

Dataset 1(Outbreak Game): CDC, US COVID-19 Vaccinations by State Dataset 2: DNA Mutations dataset from Kaggle Dataset 3: Gene Editing dataset from Kaggle Dataset 4: Antibody Blackjack dataset from Protein Data Bank

Objective

Make biotech education interactive – Use games to teach complex scientific concepts in a fun way.
Introduce machine learning – Show how AI helps in predicting diseases, designing drugs, and engineering genes.
Encourage problem-solving – Let players analyze data, make decisions, and see real-world outcomes.
Raise awareness about biotech’s impact – Highlight how biotechnology helps in medicine, genetics, and public health.
Inspire future scientists – Spark interest in STEM careers by making biotech exciting and accessible.

Roles For the project

Team 1

Project Manager/Scrum Master - Pradyun Gowda
ML Engineer - Darsh Darsh
Backend Developer - Lars Lindain
Frontend Developer - Zachary Peltz
Testing- Aarush Kota
Data Science Lead - Ian Manangan

1. Predict Outbreak Scenarios

Dataset: COVID-19 vaccinations in the US (CDC) – Vaccinations, state, distributions, daily vaccinations.
ML Model: Time-series forecasting & classification using Random Forest, XGBoost, K-Means, and Logistic Regression.
Gameplay: Players analyze trends, predict outbreaks, and implement countermeasures to minimize infections & economic impact.

Predict Outbreak Scenarios Burndown

2. DNA Building Blocks Game

Dataset: Ensembl Genome Data – nucleotide sequences and mutation data.
ML Model: Random Forest, XGBoost – predict mutation impact.
Gameplay: Players build DNA sequences; ML predicts mutation effects.

DNA Building Blocks Game Burndown

3. Gene Editing Challenge

Dataset: CRISPR/Cas9 Database – gene sequences and mutation effects.
ML Model: SVM, Random Forest – predict gene edit impacts.
Gameplay: Players modify genes; ML forecasts mutation effects.

Gene Editing Challenge Burndown

4. Antibody Blackjack

Dataset: Protein Data Bank (PDB) – antibody-antigen interactions, binding affinity scores.
ML Model: K-Nearest Neighbors, Neural Networks – predict binding efficacy and stability.
Gameplay: Players draw antibody fragments like blackjack; ML predicts if the binding score is optimal or unstable.

Antibody Blackjack Burndown

5. Cell Exploration Journey

Gameplay: Players navigate pathways through a joystick and reach different cell organelles where they learn about those organelles.

Cell Exploration Journey Burndown

6. Pathogen Platformer

Gameplay: Players run, jump, and dodge through environments infected by different pathogens. Each level represents a new infection zone. Players must:

Collect genome fragments and sequence data
Use a lab station checkpoint to classify the pathogen using AI (ML model)
Choose the right treatment or containment method (quarantine, vaccine, etc.)
Unlock the next zone if they neutralize the threat

Pathogen Platformer Burndown

Other Experiences

Various: We have other various experiences to show our work and design on our project besides just games including:

Cosmetics: A way to change your outfit before selecting a minigame
Outline: Our outline of this in our website and how we designed everything
About us: About the creators - team roles of our minigames and website