Developed and published yEscher, a comprehensive Python package for metabolic modeling and simulation specifically designed for Saccharomyces cerevisiae (baker's yeast). The package provides researchers and biotechnologists with powerful tools to analyze metabolic networks, predict cellular behavior, and optimize bioprocesses.
Technical Highlights:
- Implemented advanced algorithms for flux balance analysis (FBA) and metabolic flux analysis
- Built simulation engines for gene knockout experiments and pathway optimization
- Developed dynamic modeling capabilities for time-course metabolic predictions
- Created comprehensive visualization tools for metabolic network analysis
- Published as an open-source package with extensive documentation and test coverage
The package enables researchers to simulate complex metabolic scenarios, predict the effects of genetic modifications, and optimize fermentation processes for biotechnology applications. yEscher has been designed with computational efficiency and biological accuracy in mind, making it a valuable tool for the metabolic engineering community.