New Mexico Supercomputing Challenge

Removal of Genetic Traits from a Gene Pool

Team: 7

School: Aldo Leopold High

Area of Science: Genetics

Interim: Team Number: 007
School Name: Aldo Leopold Charter School
Area of Science: Genetics
Name Of Project: Studying the Removal of a Specific Trait from a Gene Pool
Definition of Problem:
We were originally going to explore the idea of the multiverse theory, but we decided that that would not only be very tedious work but it would include programming beyond what we are capable of for our first year of SCC. So we changed it to figuring out how many generations that it takes to remove a certain gene from the gene pool of a species in an environment. The goal of this project is to create a program that lets us visualize and determine when a gene is removed from an entire population (excluding genetic mutation).
Solution to problem:
We will simulate a population starting with many different genetic traits and see how many generations it takes to have genetic traits completely weaved out of the entire population. We will try to determine if it is possible and which genetic traits will weave out faster and why. We will test different traits, different amounts of starting population, and different environments.
Progress to date:
Currently our team is currently working on learning all we need to learn about genetics to be able to successfully simulate genetic traits and producing new population and retrieving data from the parent turtles and passing them onto the offspring turtles while simultaneously having them interact with their environment to gain and spend energy to move, reproduce, and simulating death. We have started on a basic program that supports movement and basic interaction between turtles but still need to do more research into NetLogo programming.
Expected results:
Our team expects that if it is possible that we will find a common factor between starting population and how long it takes for a genetic trait to leave the entire population, and that we will be able to infer that rate of one gene leaving the population from one population to the next.
Team members: Ian Nova, Mitchell Joy
Sponsoring teacher: Laura Larsh

Team Members:

  Mitchell Joy
  Ian Nova

Sponsoring Teacher: Laura Larisch

Mail the entire Team

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