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Showing 1 - 19 results of 19 for search '(( genes based ai optimization algorithm ) OR ( binary basic model optimization algorithm ))*', query time: 0.46s Refine Results
  1. 1
    Table 1_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.pdf

    Table 1_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.pdf by Valentina Di Salvatore (6296114)

    Published 2025
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  2. 2
    Presentation 1_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.pdf

    Presentation 1_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.pdf by Valentina Di Salvatore (6296114)

    Published 2025
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  3. 3
    Table 2_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.pdf

    Table 2_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.pdf by Valentina Di Salvatore (6296114)

    Published 2025
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  4. 4
    Image 1_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.png

    Image 1_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.png by Valentina Di Salvatore (6296114)

    Published 2025
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  5. 5
    Image 2_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.png

    Image 2_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.png by Valentina Di Salvatore (6296114)

    Published 2025
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  6. 6
    Table5_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX

    Table5_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

    Published 2023
    “…The initial implementation of the tAI had significant flaws. For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  7. 7
    Image2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG

    Image2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG by Ali Mostafa Anwar (7454504)

    Published 2023
    “…The initial implementation of the tAI had significant flaws. For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  8. 8
    Table1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX

    Table1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

    Published 2023
    “…The initial implementation of the tAI had significant flaws. For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  9. 9
    Image1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG

    Image1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG by Ali Mostafa Anwar (7454504)

    Published 2023
    “…The initial implementation of the tAI had significant flaws. For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  10. 10
    Image3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG

    Image3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG by Ali Mostafa Anwar (7454504)

    Published 2023
    “…The initial implementation of the tAI had significant flaws. For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  11. 11
    Table3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX

    Table3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

    Published 2023
    “…The initial implementation of the tAI had significant flaws. For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  12. 12
    Table4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX

    Table4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

    Published 2023
    “…The initial implementation of the tAI had significant flaws. For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  13. 13
    Table2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX

    Table2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX by Ali Mostafa Anwar (7454504)

    Published 2023
    “…The initial implementation of the tAI had significant flaws. For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  14. 14
    Image4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG

    Image4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG by Ali Mostafa Anwar (7454504)

    Published 2023
    “…The initial implementation of the tAI had significant flaws. For instance, generated S<sub>ij</sub> weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …”
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  15. 15
    Table 1_Epilepsy-associated CHD2 missense variants and optimization strategies for genetic diagnosis: a comparative analysis of algorithms.docx

    Table 1_Epilepsy-associated CHD2 missense variants and optimization strategies for genetic diagnosis: a comparative analysis of algorithms.docx by Yu-Jie Gu (20963948)

    Published 2025
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  16. 16
    Image 1_Epilepsy-associated CHD2 missense variants and optimization strategies for genetic diagnosis: a comparative analysis of algorithms.tif

    Image 1_Epilepsy-associated CHD2 missense variants and optimization strategies for genetic diagnosis: a comparative analysis of algorithms.tif by Yu-Jie Gu (20963948)

    Published 2025
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  17. 17
    Table_1_A Novel Network Pharmacology Strategy to Decode Mechanism of Lang Chuang Wan in Treating Systemic Lupus Erythematosus.xlsx

    Table_1_A Novel Network Pharmacology Strategy to Decode Mechanism of Lang Chuang Wan in Treating Systemic Lupus Erythematosus.xlsx by Yao Gao (1420339)

    Published 2020
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  18. 18
    Image_1_A Novel Network Pharmacology Strategy to Decode Mechanism of Lang Chuang Wan in Treating Systemic Lupus Erythematosus.tif

    Image_1_A Novel Network Pharmacology Strategy to Decode Mechanism of Lang Chuang Wan in Treating Systemic Lupus Erythematosus.tif by Yao Gao (1420339)

    Published 2020
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  19. 19
    Image_1_Establishment of a novel lysosomal signature for the diagnosis of gastric cancer with in-vitro and in-situ validation.tif

    Image_1_Establishment of a novel lysosomal signature for the diagnosis of gastric cancer with in-vitro and in-situ validation.tif by Qi Wang (22418)

    Published 2023
    “…</p>Conclusion<p>In summary, this study is the first to integrate around 20 mainstream ML algorithms to construct an AI-based diagnostic predictor for gastric cancer based on lysosomal-related genes. …”
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