Zobrazeno 1 - 5
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pro vyhledávání: '"Jurijs Sulins"'
Publikováno v:
Mathematical Biosciences. 307:25-32
One of use cases for metabolic network optimisation of biotechnologically applied microorganisms is the in silico design of new strains with an improved distribution of metabolic fluxes. Global stochastic optimisation methods (genetic algorithms, evo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8d7def540dcd31b16eba4feb8a11e3f
https://doi.org/10.1016/j.mbs.2018.11.002
https://doi.org/10.1016/j.mbs.2018.11.002
Autor:
Natalja Bulipopa, Jurijs Sulins
Publikováno v:
Biosystems and Information technology. 2:15-18
Many combinations of adjustable parameters should be tested in optimization experiments of biochemical networks to find the smallest subset of parameters enabling the best improvements of objective function both in case of design task and parameter e
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https://explore.openaire.eu/search/publication?articleId=doi_________::4bf9537c1346abe76baff0088f01e5d8
https://doi.org/10.11592/bit.130504
https://doi.org/10.11592/bit.130504
Publikováno v:
IEEE/ACM transactions on computational biology and bioinformatics. 14(4)
Selecting an efficient small set of adjustable parameters to improve metabolic features of an organism is important for a reduction of implementation costs and risks of unpredicted side effects. In practice, to avoid the analysis of a huge combinator
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e39bc316ee7f6cf25bd29c8fdf5db0dd
https://pubmed.ncbi.nlm.nih.gov/27071188
https://pubmed.ncbi.nlm.nih.gov/27071188
Autor:
Jurijs Sulins, Martins Mednis
Publikováno v:
Biosystems and Information technology. 1:1-5
Dynamic models give detailed information about the influence of many parameters on the behaviour of the biochemical process of interest. Parameter optimization of dynamic models is used in parameter estimation tasks and in design tasks. A drawback of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e20b285c549c88e237a52a308958f07
https://doi.org/10.11592/bit.120501
https://doi.org/10.11592/bit.120501
Publikováno v:
2012 IEEE 13th International Symposium on Computational Intelligence and Informatics (CINTI).
A disadvantage of global stochastic optimization methods is the stochastic convergence of the best value of the objective function to the global optimum. In spite those methods are widely used optimizing kinetic models of biochemical pathways. Moreov
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https://explore.openaire.eu/search/publication?articleId=doi_________::a7c203e21674ed9ccb703393c929e457
https://doi.org/10.1109/cinti.2012.6496792
https://doi.org/10.1109/cinti.2012.6496792