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algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
algorithm steps » algorithm shows (Expand Search), algorithm models (Expand Search)
python function » protein function (Expand Search)
steps function » step function (Expand Search), its function (Expand Search), cep function (Expand Search)
algorithm pre » algorithm where (Expand Search), algorithm used (Expand Search), algorithm from (Expand Search)
pre function » spread function (Expand Search), sphere function (Expand Search), three function (Expand Search)
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1621
Table_4_High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.XLSX
Published 2019“…On the one hand, the high-order Pearson's correlation coefficient can highlight the latent patterns underlying noisy input datasets and thus improve the accuracy and robustness of the algorithms currently available for sample clustering. …”
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1622
DataSheet1_Identification of potential auxin response candidate genes for soybean rapid canopy coverage through comparative evolution and expression analysis.zip
Published 2024“…Further development of this and similar algorithms for defining and quantifying tissue- and phenotype-specificity in gene expression may allow expansion of diversity in valuable phenotypes in important crops.…”
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1623
Table_2_High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.XLSX
Published 2019“…On the one hand, the high-order Pearson's correlation coefficient can highlight the latent patterns underlying noisy input datasets and thus improve the accuracy and robustness of the algorithms currently available for sample clustering. …”
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1624
Table_1_High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.docx
Published 2019“…On the one hand, the high-order Pearson's correlation coefficient can highlight the latent patterns underlying noisy input datasets and thus improve the accuracy and robustness of the algorithms currently available for sample clustering. …”
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1625
Table_3_High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.XLS
Published 2019“…On the one hand, the high-order Pearson's correlation coefficient can highlight the latent patterns underlying noisy input datasets and thus improve the accuracy and robustness of the algorithms currently available for sample clustering. …”
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1626
Image_2_Prioritizing Molecular Biomarkers in Asthma and Respiratory Allergy Using Systems Biology.jpeg
Published 2021“…Here, we analyze our experimental results using complex algorithmic approaches that establish holistic disease models (systems biology), combining these insights with information available in specialized databases developed worldwide. …”
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1627
Table_5_High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.XLSX
Published 2019“…On the one hand, the high-order Pearson's correlation coefficient can highlight the latent patterns underlying noisy input datasets and thus improve the accuracy and robustness of the algorithms currently available for sample clustering. …”
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1628
Image_1_Prioritizing Molecular Biomarkers in Asthma and Respiratory Allergy Using Systems Biology.jpeg
Published 2021“…Here, we analyze our experimental results using complex algorithmic approaches that establish holistic disease models (systems biology), combining these insights with information available in specialized databases developed worldwide. …”
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1629
DataSheet_1_Prioritizing Molecular Biomarkers in Asthma and Respiratory Allergy Using Systems Biology.pdf
Published 2021“…Here, we analyze our experimental results using complex algorithmic approaches that establish holistic disease models (systems biology), combining these insights with information available in specialized databases developed worldwide. …”