Showing 1 - 20 results of 209 for search '(( genes based active optimization algorithm ) OR ( binary based whale optimization algorithm ))', query time: 0.70s Refine Results
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    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
    “…Differential gene expression analysis identified compartment-specific transcriptional responses, which were then used to construct a risk index based on predicted immune activation and the number of upregulated immune markers. …”
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    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
    “…Differential gene expression analysis identified compartment-specific transcriptional responses, which were then used to construct a risk index based on predicted immune activation and the number of upregulated immune markers. …”
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    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
    “…Differential gene expression analysis identified compartment-specific transcriptional responses, which were then used to construct a risk index based on predicted immune activation and the number of upregulated immune markers. …”
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    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
    “…Differential gene expression analysis identified compartment-specific transcriptional responses, which were then used to construct a risk index based on predicted immune activation and the number of upregulated immune markers. …”
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    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
    “…Differential gene expression analysis identified compartment-specific transcriptional responses, which were then used to construct a risk index based on predicted immune activation and the number of upregulated immune markers. …”
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    MultiCRISPR-EGA: Optimizing Guide RNA Array Design for Multiplexed CRISPR Using the Elitist Genetic Algorithm by Yangyu Zhang (4609117)

    Published 2025
    “…Recognizing that more stable gRNAs, characterized by lower minimum free energy (MFE), have prolonged activity and thus higher efficacy, we developed MultiCRISPR-EGA, a graphical user interface (GUI)-based tool that employs the Elitist Genetic Algorithm (EGA) to design optimized single-promoter-driven multiplexed gRNA arrays. …”
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    Stochastic simulation and statistical inference platform for visualization and estimation of transcriptional kinetics by Gennady Gorin (8466255)

    Published 2020
    “…As a demonstration, we show that the optimization algorithm can successfully recover the transcriptional kinetics of simulated and experimental gene expression data. …”
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    Raw Data for the Thesis: "<i>Enhancing RNAi-Based Pest Control through Effective Target Gene Selection and Optimal dsRNA Design</i>" by Doga CEDDEN (12675286)

    Published 2025
    “…</p><p><br></p><p dir="ltr">Chapter 4 introduces the dsRIP web platform (<a href="https://dsrip.uni-goettingen.de/" target="_blank">https://dsrip.uni-goettingen.de/</a>) for designing sequence-optimized dsRNA for RNAi-based pest control. In the experimental part, small interfering RNA (siRNA) features that were associated with RNAi efficacy in human cells were tested in <i>T. castaneum </i>by targeting an essential gene and measuring insecticidal efficacy. …”
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    Table1_Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO.docx by Haohan Xue (17892128)

    Published 2024
    “…The problem of multi-parameter optimization introduced in the support vector regression model was solved by the particle swarm optimization algorithm. …”
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