Dear StrainDesign team,
When using SD with gene-level interventions (with sd.ANY), the returned gene_sd solutions sometimes contain gene knockouts that have no metabolic effect. Specifically, a gene KO is included in the gene_sd even though the corresponding reaction_sd contains no reaction KO for any of the associated reactions. The reaction level designs seem to meet the requirements imposed by the suppress and protect modules so the solutions don't appear to be problematic. In case this is relevant, during running straindesign the following message was printed regarding the trimming of some variables "One of the generated reaction names is beyond or close to the limit of 255 characters permitted by GLPK and Gurobi.".
A brief investigation with AI tools points between a mismatch in how the interventions are treated in the optimization vs the reporting space.
Environment used:
SD: v1.18
Solver: gurobi
Model: iML1515 (with modifications that shouldn't affect the gpr rules)
gko_cost, ko_cost and ki_cost included in the problem formulation with an associated cost=1 in every case.
the solutions objects were accessed through sols.gene_sd and sols.reaction_sd with sols being the sd.compute_strain_designs object.
Let me know if any further information is required on my end,
Best,
Vasilis
Dear StrainDesign team,
When using SD with gene-level interventions (with sd.ANY), the returned gene_sd solutions sometimes contain gene knockouts that have no metabolic effect. Specifically, a gene KO is included in the gene_sd even though the corresponding reaction_sd contains no reaction KO for any of the associated reactions. The reaction level designs seem to meet the requirements imposed by the suppress and protect modules so the solutions don't appear to be problematic. In case this is relevant, during running straindesign the following message was printed regarding the trimming of some variables "One of the generated reaction names is beyond or close to the limit of 255 characters permitted by GLPK and Gurobi.".
A brief investigation with AI tools points between a mismatch in how the interventions are treated in the optimization vs the reporting space.
Environment used:
SD: v1.18
Solver: gurobi
Model: iML1515 (with modifications that shouldn't affect the gpr rules)
gko_cost, ko_cost and ki_cost included in the problem formulation with an associated cost=1 in every case.
the solutions objects were accessed through sols.gene_sd and sols.reaction_sd with sols being the sd.compute_strain_designs object.
Let me know if any further information is required on my end,
Best,
Vasilis