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Record W2063795543 · doi:10.2202/1542-6580.1326

A Structured Model for Interleukin-11 Production with Recombinant <i>E.coli</i> and Genetic Algorithm for Model Parameter Estimation

2006· article· en· W2063795543 on OpenAlexafffund
Shuiquan Tang, Zi‐Sheng Zhang, Yiru Gan

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicViral Infectious Diseases and Gene Expression in Insects
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBioprocessRecombinant DNAEscherichia coliFermentationBiochemical engineeringGenetic algorithmProduction (economics)BiologyBiological systemComputational biologyComputer scienceBiotechnologyMicrobiologyMathematicsMathematical optimizationFood scienceEngineeringBiochemistryGene

Abstract

fetched live from OpenAlex

Recombinant human interleukin-11(rhIL-11) is still the only therapy drug for thrombocytopenia. Although the biological properties and clinical behaviors of rhIL-11 have been studied extensively, bioprocess development work has rarely been reported. In this study, a three-compartment structured model was developed to simultaneously simulate batch cultivation of bacteria growth, substrate utilization and intracellular rhIL-11 production with recombinant E. coli. A genetic algorithm was formulated and successfully applied to the estimation of the model parameters, which simulated the experimental data obtained from flask cultivation experiments quite well. The results of this work indicate that combination of structured modeling and genetic algorithm could be a simple and effective way for simulating the fermentation of recombinant microorganisms with over-production of foreign proteins.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.234
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Chemical Reactor EngineeringSame topicViral Infectious Diseases and Gene Expression in InsectsFrench-language works237,207