New Mexico Supercomputing Challenge

Micro-Revolution

Team: 50

School: La Cueva High

Area of Science: Genetics


Interim: Problem definition:
One of the biggest problems in modern medicine is the ever increasing fear of bacterial resistance. When antibiotics are used, especially overused, most of the bacteria being targeted in the infected person will die, but due to the mutation and evolution of bacteria, some bacteria will be resistant to the antibiotic, and will be able to reproduce thus giving rise to resistant bacteria.

Problem solution:
The final goal with our project is to use computer programming to construct a model of bacteria becoming resistant over time. This model would work based off of inputs from a graphical user interface that allows the user to change the agents that directly influence the speed at which bacteria mutate and become genetically diverse. Of course, there is no set mathematical formula for bacterial resistance because of the sheer amount of factors, so the model will be based off of approximations in many regards. Not every factor can be accurately and quantitatively measured, so some of the the inputs will be specific while others will be relative values (such as the spread rate of bacteria in a population). We intend to test the accuracy of our approximations with known and heavily studied bacteria that have become resistant to certain antibiotics.

Progress to date:
Currently, we have brainstormed a solid idea for exactly what we want from our program, and have set a course for our team to try our best to catch up to where we should be, because we understand the extent to which we have unfortunately fallen behind. So far, we have been able to start on the user interface while working to get the many kinks out of the biomathematical computations in our project. We have found a contact that we are going to pursue to find necessary information on how certain factors will affect the estimation we are trying to achieve.
We have had a very hard time finding good approximations, and have found several more factors than we initially anticipated. Unfortunately it seems that the coolness of the projects that we initially considered are inversely proportional to their feasibility. Regardless, we are still very interested in what we can do with this project and want to pursue the idea, despite the barriers.

Expected results:
Seeing as though the process of evolution is extremely complicated and mutation is based on probability, approximations will rarely have the potential to be very accurate. We hope that we can work out the kinks previously mentioned to a point such that we can input information from bacteria that have already become resistant to certain antibiotics, and get returns that match a similar amount of time it takes bacteria to become resistant.

We would like to thank Mr. Jason Dewitte for his constant willingness to help and Mr. Samuel Smith for sticking with us through our falling behind and encounters with several barriers.

Team 50 - Members: Colton Paul, Eric Sivonxay, Rana Chan, and Alex Johnson


Team Members:

  Colton Paul
  Eric Sivonxay
  Rana Chan
  Alex Johnson

Sponsoring Teacher: Samuel Smith

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