Selected article for: "discovery rate and human proteome"

Author: Kevin Dick; Kyle K Biggar; James R Green
Title: Computational Prediction of the Comprehensive SARS-CoV-2 vs. Human Interactome to Guide the Design of Therapeutics
  • Document date: 2020_3_31
  • ID: dxabs45r_53
    Snippet: Of the 225 human proteins within the intersection of the PIPE4 and SPRINT predicted interactions, we ran a number of GO-term analyses to better understand the functional role of the human proteins involved. To this end, the GO Panther Classification System was used to run over/under-representation analysis of the 225 human proteins as compared to the reference human proteome. A Fisher's Exact test with correction for False Discovery Rate was used.....
    Document: Of the 225 human proteins within the intersection of the PIPE4 and SPRINT predicted interactions, we ran a number of GO-term analyses to better understand the functional role of the human proteins involved. To this end, the GO Panther Classification System was used to run over/under-representation analysis of the 225 human proteins as compared to the reference human proteome. A Fisher's Exact test with correction for False Discovery Rate was used to extract a list of the most enriched GO-terms among the 215 human proteins for which GO-term data were available. The Molecular Functions exhibiting a fold enrichment greater than 3 are reported in 5; the Biological Processes exhibiting a fold enrichment greater than 50 are reported in 6; and the Cellular Components exhibiting a fold enrichment greater than 15 are reported in 7. The fold enrichment cut-offs were selected to limit the size of the tables; the complete tables are available in the public repository, [10] .

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