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Unique identifier OMICS_06457
Name EMILiO

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Publication for EMILiO

EMILiO citations

 (7)
library_books

Genome scale modeling of yeast: chronology, applications and critical perspectives

2017
FEMS Yeast Res
PMCID: 5812505
PMID: 28899034
DOI: 10.1093/femsyr/fox050

[…] e consideration of gene deletions together with heterologous insertions—using mixed-integer programming methods (OptStrain: Pharkya, Burgard and Maranas )—or gene expression levels (OptReg, OptForce, EMILio: Pharkya and Maranas ; Ranganathan, Suthers and Maranas ; Yang, Cluett and Mahadevan ), to the exploitation of transcriptional regulatory targets—using integrated (OptORF: Kim and Reed ) or uni […]

library_books

Quantifying complexity in metabolic engineering using the LASER database

2016
Metab Eng Com
PMCID: 5779719
PMID: 29468127
DOI: 10.1016/j.meteno.2016.07.002

[…] metrics can be applied to proposed strains identified by computational strain design algorithms to identify the least complex designs achieving the desired performance (yield). In one such study, the EMiLIO algorithm was used to generate 234 designs with enhanced succinate yield under aerobic and anaerobic conditions, compared to wild-type E. coli (). Complexity arises both from the number of reac […]

library_books

Computational approaches to metabolic engineering utilizing systems biology and synthetic biology

2014
Comput Struct Biotechnol J
PMCID: 4212286
PMID: 25379141
DOI: 10.1016/j.csbj.2014.08.005

[…] ptORF , OptFlux , and OptForce .In addition to the family of algorithms related to OptKnock, there have been numerous variant algorithms developed to address computational or algorithmic limitations. EMILiO was developed as a computationally efficient algorithm for searching through a broader range of possible genetic manipulations. CosMos developed designs for a variety of manipulations, but co […]

library_books

Proteomics based metabolic modeling and characterization of the cellulolytic bacterium Thermobifida fusca

2014
BMC Syst Biol
PMCID: 4236713
PMID: 25115351
DOI: 10.1186/s12918-014-0086-2

[…] gineering to yield products of biotechnological value []. The most widely-used algorithms for design and simulation of genome-scale constraint-based metabolic models such as OptKnock [], OptForce [], EMiLio [] are based on flux distribution and flow through chemically balanced reactions (FBA). Flux balance analysis (FBA) uses linear programming to optimize the objective function as follows:(1)Maxi […]

library_books

Dynamic strain scanning optimization: an efficient strain design strategy for balanced yield, titer, and productivity. DySScO strategy for strain design

2013
BMC Biotechnol
PMCID: 3574860
PMID: 23388063
DOI: 10.1186/1472-6750-13-8

[…] envelope using dFBA, an optimal range of growth rates can be determined based on the desired design criteria. Then, during the “design” phase, existing strain-design algorithms (e.g. OptKnock, GDLS, EMILiO) can be used to find the potential strains with high product yield within this growth rate range. Lastly, during the “selection” phase, dFBA simulations of these potential strains are performed […]

library_books

Stoichiometric capacitance reveals the theoretical capabilities of metabolic networks

2012
Bioinformatics
PMCID: 3436808
PMID: 22962473
DOI: 10.1093/bioinformatics/bts381

[…] ed systematic investigations of network modifications directed at enhancing the production of selected targets. For instance, OptKnock (), OptStrain (), OptReg (), OptForce () and CASOP () as well as EMILiO () have facilitated prediction and in silico verification of network modifications, including insertion and deletion of reactions from other species or under-and over-expression of gene product […]


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EMILiO institution(s)
Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Canada

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