Welcome to cameo!¶
What is cameo?¶
Cameo is a high-level python library developed to aid the strain design process in metabolic engineering projects. The library provides a modular framework of simulation and strain design methods that targets developers that want to develop new design algorithms and custom analysis workflows. Furthermore, it exposes a high-level API to users that just want to compute promising strain designs.
Curious? Head over to try.cameo.bio and give it a try.
Please cite https://doi.org/10.1021/acssynbio.7b00423 if you’ve used cameo in a scientific publication.
High-level API (for users)¶
Compute strain engineering strategies for a desired product in a number of host organisms using the high-level interface (runtime is on the order of hours).
from cameo.api import design design(product='L-Serine')
The high-level API can also be called from the command line.
$ cameo design vanillin
For more information run
$ cameo --help
Low-level API (for developers)¶
Find gene knockout targets using evolutionary computation.
from cameo import models from cameo.strain_design.heuristic import GeneKnockoutOptimization from cameo.strain_design.heuristic.objective_functions import biomass_product_coupled_yield model = models.bigg.e_coli_core obj = biomass_product_coupled_yield( model.reactions.Biomass_Ecoli_core_w_GAM, model.reactions.EX_succ_e, model.reactions.EX_glc_e) ko = GeneKnockoutOptimization(model=model, objective_function=obj) ko.run(max_evaluations=50000, n=1, mutation_rate=0.15, indel_rate=0.185)
Predict heterologous pathways for a desired chemical.
from cameo.strain_design import pathway_prediction predictor = pathway_prediction.PathwayPredictor(model) pathways = predictor.run(product="vanillin")