Bayesian Modeling in Biotech: Using PyMC to Analyze Agricultural Data


AUTHORED BY

Thomas Wiecki

DATE

2022-08-11


Introduction

In July 2022, we organized a panel discussion with Manu Martinet of Indigo Ag and Thomas Wiecki and Bill Engels of PyMC Labs to discuss a case-study of measuring effects of crop-types in an agricultural setting. The goal of the project was to identify the underlying spatial pattern and remove it in order to measure more accurately the treatment effect, which in this case are microbes which contribute to plant yield.

PyMC Labs were consultants on this project which had limited data and which used Bayesian analyses and Gaussian processes to identify the treatment effect. We demonstrate how Bayesian modeling is a powerful tool for solving problems in biotechnology.




Work with PyMC Labs

If you are interested in seeing what we at PyMC Labs can do for you, then please email info@pymc-labs.io. We work with companies at a variety of scales and with varying levels of existing modeling capacity. We also run corporate workshop training events and can provide sessions ranging from introduction to Bayes to more advanced topics.