Biology subjects
Publications and source records attributed to Matthew Theisen.
The py_emra module implements the Ensemble Modeling Robustness Analysis (EMRA) algorithm in Python. Previous implementations in MATLAB have been used to gain useful insights into metabolic dynamics and metabolic engineering strategies. The py_emra package performs favorably in comparison to MATLAB. Potential extensions and improvements are discussed.
The stability of the Calvin Bassham Benson (CBB) cycle remains an area of active computational research. Our understanding of biology and the prospect for bioengineered plants with higher productivity may both be impacted by a greater understanding of this area. Here we use the ensemble modelling robustness analysis (EMRA) framework to show that the action of the phosphate/G3P antiporter is much more significant for maintenance of stability than a recently proposed G6P shunt. Additionally, we interpret recent results suggesting that overexpression of RuBiSCO does not improve growth rate of plants but overexpression of SBPase does. Our simulations reproduce this result, but only in models which do not include the G6P shunt. Taken together, these results may suggest a situational role for the G6P shunt, possibly in dynamic situations under starvation or other stress conditions.