This repository enables solving the multiobjective biocatalytic strain design problem (ModCell) with different Multiobjective evolutionary algorithms (MOEA). An analysis pipeline to compare the performance of different MOEAs is also included.
If you use any part of this software please cite:
Garcia, S. & Trinh, C. T. Comparison of Multi-Objective Evolutionary Algorithms to Solve the Modular Cell Design Problem for Novel Biocatalysis. Processes 7, (2019).
Here is the citation in bibtex format:
@Article{ garcia2019c,
author = {Garcia, Sergio and Trinh, Cong T.},
title = {Comparison of Multi-Objective Evolutionary Algorithms to
Solve the Modular Cell Design Problem for Novel
Biocatalysis},
journal = {Processes},
volume = {7},
year = {2019},
number = {6},
article-number= {361},
url = {https://www.mdpi.com/2227-9717/7/6/361},
issn = {2227-9717},
abstract = {A large space of chemicals with broad industrial and
consumer applications could be synthesized by engineered
microbial biocatalysts. However, the current strain
optimization process is prohibitively laborious and costly
to produce one target chemical and often requires new
engineering efforts to produce new molecules. To tackle
this challenge, modular cell design based on a chassis
strain that can be combined with different product
synthesis pathway modules has recently been proposed. This
approach seeks to minimize unexpected failure and avoid
task repetition, leading to a more robust and faster strain
engineering process. In our previous study, we
mathematically formulated the modular cell design problem
based on the multi-objective optimization framework. In
this study, we evaluated a library of state-of-the-art
multi-objective evolutionary algorithms (MOEAs) to identify
the most effective method to solve the modular cell design
problem. Using the best MOEA, we found better solutions for
modular cells compatible with many product synthesis
modules. Furthermore, the best performing algorithm could
provide better and more diverse design options that might
help increase the likelihood of successful experimental
implementation. We identified key parameter configurations
to overcome the difficulty associated with multi-objective
optimization problems with many competing design
objectives. Interestingly, we found that MOEA performance
with a real application problem, e.g., the modular strain
design problem, does not always correlate with artificial
benchmarks. Overall, MOEAs provide powerful tools to solve
the modular cell design problem for novel biocatalysis.},
doi = {10.3390/pr7060361}
}
- Ensure that you meet the following dependencies:
- The release v1.1 or greater of the ModCell package must be in your matlab path.
- matlab_utils, used to make figures.
- Simply add the
compare-moeafiles to your matlab path.
Open an issue if you encounter an error or need assitance.
Two external packages are included in this repository:
- PlatEMO (This package has been modified to enable ModCell compatibility and fix some errors)
- Hypervolume calculator from Fonseca et al.