Selected article for: "gene expression and individual expression"

Author: Tristan de Jong; Victor Guryev; Yury M. Moshkin
Title: Discovery of pharmaceutically-targetable pathways and prediction of survivorship for pneumonia and sepsis patients from the view point of ensemble gene noise
  • Document date: 2020_4_11
  • ID: f5w05rc2_27
    Snippet: As compared to DGE, ensemble gene noise provides a holistic interpretation to mis-regulation in gene expression under pathologic or other conditions. As it operates on the level of gene ensembles it does not require gene set enrichment analysis (GSEA), thus it circumvents potential pitfalls of GSEA associated with the cut-off problem of DGE [24, 25] . As any gene expression analysis ensemble gene noise relies on the quality and completeness of pa.....
    Document: As compared to DGE, ensemble gene noise provides a holistic interpretation to mis-regulation in gene expression under pathologic or other conditions. As it operates on the level of gene ensembles it does not require gene set enrichment analysis (GSEA), thus it circumvents potential pitfalls of GSEA associated with the cut-off problem of DGE [24, 25] . As any gene expression analysis ensemble gene noise relies on the quality and completeness of pathways and the protein complexes' annotation. Finally, we noted that inter-individual variability of ensemble gene noise is significantly less than that of individual gene expression ( Figure S3 ). This, in turn, might improve the accuracy of diagnostic and clinical outcome models. Though it might come at the expense of less features being available for the selection and training of models. At the same time, in future studies, both DGE and ensemble gene noise could be combined.

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