ModelSEEDpy: A Python Framework to Build Genome Scale Metabolic Models

Abstract: Genome scale metabolic models (GEM) are used in a broad range of applications in biology, such as strain engineering, knowledge discovery, species interactions, etc. As of today, there are several platforms to build metabolic models, and the two most dominant are the COBRA toolbox for MATLAB and COBRApy for python. The COBRA toolbox offers a rich framework with many features to assist model reconstruction. However, it depends on MATLAB, while COBRApy provides a solid framework for GEM analysis but it does not provide reconstruction methods.

In this presentation, we introduce the ModelSEEDpy, a python library to build genome scale metabolic models, it includes classification, reconstruction, ATP profiling/correction and extensions (e.g., visualization, KBase interaction). We show our approach to enhance the traditional model reconstruction approach to split the process into multiple steps to differentiate species.