Overview

Models are essential tools for gathering insights and predicting outcomes of various different biological processes. In this section we explore some quantifiable aspects of our project which gives an overall idea about the biocontrol agent from its development to application in fields and even future modification suggestions.

We start with developing a monte-carlo type simulation model for the cas protein insertion in the OMVs. After that we model the bacterial biofilm degradation by using a Reaction-Diffusion PDE. How much our bio-control will be effective in a real life scenario is then tested with the help of our population dynamics model. Taking inputs from our biomodellers we built a novel kinetic model of the Riboswitch which quantifies and theoretically verifies the working of the detection kit. Taking the help of recent literature, we implemented a statistical mechanics inspired machine learning model that helped us predict the future mutations of a given sequence of XopN data for Xanthomonas. Finally we finish by giving an outline for how to quantify our proposed Kill switch model.