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A Hybrid of Particle Swarm Optimization and Minimization of Metabolic Adjustment for Ethanol Production of Escherichia Coli.

, , , , , , , , and . PACBB, volume 1005 of Advances in Intelligent Systems and Computing, page 36-44. Springer, (2019)

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Identifying Metabolic Pathway within Microarray Gene Expression Data Using Combination of Probabilistic Models., and . KTW, volume 295 of Communications in Computer and Information Science, page 52-61. Springer, (2011)Prediction of Protein Residue Contact Using Support Vector Machine., and . KTW, volume 295 of Communications in Computer and Information Science, page 323-332. Springer, (2011)Random Forest for Gene Selection and Microarray Data Classification., and . KTW, volume 295 of Communications in Computer and Information Science, page 174-183. Springer, (2011)Identifying Gene Knockout Strategy Using Bees Hill Flux Balance Analysis (BHFBA) for Improving the Production of Succinic Acid and Glycerol in Saccharomyces cerevisiae., , , , , and . PAKDD Workshops, volume 7867 of Lecture Notes in Computer Science, page 223-233. Springer, (2013)Parameter Estimation Using Improved Differential Evolution (IDE) and Bacterial Foraging Algorithm to Model Tyrosine Production in Mus Musculus (Mouse)., , , , , , and . PAKDD Workshops, volume 7867 of Lecture Notes in Computer Science, page 179-190. Springer, (2013)Review and Analysis of Patients' Body Language From an Artificial Intelligence Perspective., , , , , , , and . IEEE Access, (2023)Using Ant Colony Optimization (ACO) on Kinetic Modeling of the Acetoin Production in Lactococcus Lactis C7., , , , , , , and . BDI, volume 477 of Studies in Computational Intelligence, page 25-35. Springer, (2013)Inferring E. coli SOS Response Pathway from Gene Expression Data Using IST-DBN with Time Lag Estimation., , , , and . BDI, volume 477 of Studies in Computational Intelligence, page 5-14. Springer, (2013)Optimizing Ethanol Production in Escherichia Coli Using a Hybrid of Particle Swarm Optimization and Artificial Bee Colony., , , , and . ICAAI, page 140-146. ACM, (2022)Multiple Gene Sets for Cancer Classification Using Gene Range Selection Based on Random Forest., , and . ACIIDS (1), volume 7802 of Lecture Notes in Computer Science, page 385-393. Springer, (2013)