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significant use » significant cause (Expand Search), significant i.e (Expand Search), significantly used (Expand Search)
fold decrease » fold increase (Expand Search), fold increased (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), mean decrease (Expand Search)
use based » rule based (Expand Search), case based (Expand Search), one based (Expand Search)
Showing 161 - 180 results of 117,810 for search '(( significant use based ) OR ( significant ((fold decrease) OR (nn decrease)) ))', query time: 1.02s Refine Results
  1. 161
    DNA concentrations of ucfDNA across WT, <i>Dnase1l3</i><sup>-/-</sup> and <i>Dnase1</i><sup><i>-/-</i></sup> mice with quantifiable ucfDNA using Qubit assay.

    DNA concentrations of ucfDNA across WT, <i>Dnase1l3</i><sup>-/-</sup> and <i>Dnase1</i><sup><i>-/-</i></sup> mice with quantifiable ucfDNA using Qubit assay. by Meihui Chen (1670020)

    Published 2022
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  2. 162
    Overview of the study design.

    Overview of the study design. by Meihui Chen (1670020)

    Published 2022
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  3. 163
    The end density of ucfDNA across different tissue types.

    The end density of ucfDNA across different tissue types. by Meihui Chen (1670020)

    Published 2022
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  4. 164
    End density of the ucfDNA fragments within the DHSs.

    End density of the ucfDNA fragments within the DHSs. by Meihui Chen (1670020)

    Published 2022
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  5. 165
    Percentages of ucfDNA fragments starting with T.

    Percentages of ucfDNA fragments starting with T. by Meihui Chen (1670020)

    Published 2022
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  6. 166
    Comparison of <i>DNASE1</i> mRNA expression levels in bladder tumoral tissues (n = 41) and adjacent non-tumoral tissues (n = 19) using the TCGA dataset.

    Comparison of <i>DNASE1</i> mRNA expression levels in bladder tumoral tissues (n = 41) and adjacent non-tumoral tissues (n = 19) using the TCGA dataset. by Meihui Chen (1670020)

    Published 2022
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  7. 167
    S8 Fig -

    S8 Fig - by Meihui Chen (1670020)

    Published 2022
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  8. 168
    DNA concentrations of ucfDNA in WT, <i>Dnase1l3</i><sup>-/-</sup> and <i>Dnase1</i><sup>-/-</sup> mice.

    DNA concentrations of ucfDNA in WT, <i>Dnase1l3</i><sup>-/-</sup> and <i>Dnase1</i><sup>-/-</sup> mice. by Meihui Chen (1670020)

    Published 2022
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  9. 169
    S5 Fig -

    S5 Fig - by Meihui Chen (1670020)

    Published 2022
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  10. 170
    Western blot and zymogram analysis of DNASE1 and DNASE1L3 in urine and plasma samples from healthy human subjects and C57BL/6 mice.

    Western blot and zymogram analysis of DNASE1 and DNASE1L3 in urine and plasma samples from healthy human subjects and C57BL/6 mice. by Meihui Chen (1670020)

    Published 2022
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  11. 171
    Jagged index-unmethylated (JI-U) values of ucfDNA.

    Jagged index-unmethylated (JI-U) values of ucfDNA. by Meihui Chen (1670020)

    Published 2022
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  12. 172
    Proportion of human ucfDNA molecules falling within the DHSs.

    Proportion of human ucfDNA molecules falling within the DHSs. by Meihui Chen (1670020)

    Published 2022
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  13. 173
    Significant difference examined in the ranking of PIQE.

    Significant difference examined in the ranking of PIQE. by Shigeaki Higashiyama (20308733)

    Published 2024
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  14. 174
    All significantly enriched pathways obtained from GSEA based on GSE10334.

    All significantly enriched pathways obtained from GSEA based on GSE10334. by Bo Zhao (13553)

    Published 2025
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  15. 175
    All significantly enriched pathways obtained from GSEA based on GSE43525.

    All significantly enriched pathways obtained from GSEA based on GSE43525. by Bo Zhao (13553)

    Published 2025
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  16. 176
    Significance analysis results.

    Significance analysis results. by Yicheng Long (366418)

    Published 2025
    “…<div><p>Amid substantial capital influx and the rapid evolution of online user groups, the increasing complexity of user behavior poses significant challenges to cybersecurity, particularly in the domain of vulnerability prediction. …”
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  17. 177
    Chemical identification of the 14 significantly different VOCs used to correctly classify the strains of the selected bacteria.

    Chemical identification of the 14 significantly different VOCs used to correctly classify the strains of the selected bacteria. by Kim F. H. Hintzen (17854597)

    Published 2024
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  18. 178
    The top 10 putative metabolites with the largest negative fold change between normal and thin cows.

    The top 10 putative metabolites with the largest negative fold change between normal and thin cows. by Bhuripit Saraphol (20855573)

    Published 2025
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  19. 179
    The top 10 putative metabolites with the largest positive fold change between normal and thin cows.

    The top 10 putative metabolites with the largest positive fold change between normal and thin cows. by Bhuripit Saraphol (20855573)

    Published 2025
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  20. 180
    Significant AKI-correlated isolated medications.

    Significant AKI-correlated isolated medications. by Wenjun Zhu (289128)

    Published 2023
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