Overview

Although our team did not develop specialized software tailored to this project, and we would not complete for the software award, we explored several approaches during our modeling efforts.

Attempted Molecular Dynamics

Initially, we attempted to construct a molecular dynamics model to predict the probability of target gene expression during the transformation of Chlamydomonas reinhardtii using plasmid C (which we were unable to synthesize). However, due to our team’s limited expertise and technical background in molecular dynamics, this approach proved unfeasible.

Statistical & Computational Modeling

Consequently, we shifted to a modeling strategy based on statistical and computational methods. Using data from the literature, we estimated the probabilities of individual events in the expression process, treating them as a continuous sequence to infer the overall success rate. Building on this framework, and with the assistance of ChatGPT 5.0, we developed a Python program capable of running 10,000 Monte Carlo simulations. Detailed instructions for using this program can be found on the “Model” page of our wiki.

Significance

We believe that, although this was only a modest attempt, it was highly meaningful for our team. We hope that this modeling exploration will not only serve as a valuable step in our own practice of modeling and software development, but also provide certain useful insights for future iGEM teams.