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Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

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Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
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Routh-Hurwitz Criterion I01:15

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Consider an electrical power grid, where stability is essential to prevent blackouts. The Routh-Hurwitz criterion is a valuable tool for assessing system stability under varying load conditions or faults. By analyzing the closed-loop transfer function, the Routh-Hurwitz criterion helps determine whether the system remains stable.
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Related Experiment Video

Updated: Feb 7, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
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Microarray-Based Quality Assessment as a Supporting Criterion for de novo Transcriptome Assembly Selection.

Patricia Carvajal-Lopez, Fernando D Von Borstel, Amada Torres

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |July 31, 2018
    PubMed
    Summary
    This summary is machine-generated.

    Selecting the best RNA-Sequencing de novo assembly is challenging. Mapping DNA microarray hybridized probes offers a reliable method for quality assessment, outperforming traditional metrics for identifying superior assemblies.

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    DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning
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    Area of Science:

    • Genomics
    • Bioinformatics
    • Transcriptomics

    Background:

    • RNA-Sequencing (RNA-Seq) and de novo assembly are crucial for analyzing species lacking reference transcriptomes.
    • However, biological and technical factors introduce errors during assembly reconstruction.
    • Selecting the optimal assembly from multiple reconstructions generated by varying parameters remains a significant challenge.

    Purpose of the Study:

    • To propose and validate a novel criterion for selecting the best de novo transcriptome assembly.
    • To evaluate the effectiveness of mapping DNA microarray hybridized probes for assembly quality assessment.
    • To compare the proposed criterion with traditional quantitative metrics.

    Main Methods:

    • RNA-Seq datasets from mouse and fruit fly were used for de novo assembly.
    • Multiple assembly reconstructions were generated by varying assembly parameters.
    • Assembly quality was assessed using standard quantitative metrics and the proposed probe mapping criterion.
    • Statistical analysis (ANOVA) was employed to determine significance.

    Main Results:

    • The proposed criterion, based on mapping hybridized probes, successfully identified the highest quality assemblies.
    • Probe mapping outperformed inconsistent quantitative metrics in distinguishing superior assemblies.
    • A statistically significant (p < 0.05) 0.25% probe mapping difference enabled selection of an assembly yielding 3,719 more contigs and 1,049 additional mapped contigs in mouse.
    • The best assembly consistently showed the highest mapping rate to reference transcriptomes.

    Conclusions:

    • Mapping DNA microarray hybridized probes provides a robust and reliable method for selecting optimal de novo transcriptome assemblies.
    • This criterion is particularly valuable when traditional quantitative metrics yield inconsistent results.
    • The approach is suitable for quality assessment of multiple de novo assembly strategies, especially for non-model species with available microarray data.