Selected article for: "linear regression problem and steady state"
Author: Noh, Heeju; Shoemaker, Jason E; Gunawan, Rudiyanto
Title: Network perturbation analysis of gene transcriptional profiles reveals protein targets and mechanism of action of drugs and influenza A viral infection
  • Document date: 2018_4_6
    • ID: j80hnhpb_22
    Snippet: where s ki is the time derivatives (slope) of the log 2 FC of gene k in sample i. In contrast to Equation (4), Equation (5) was derived without assuming pseudo steady-state, which was necessary to account for the dynamics of gene expressions. The slopes of the log 2 FC at each sampling time point were computed using a second-order accurate finite difference approximation (37) . In summary, the estimation of edge weights in ProTINA involved the fo.....
    Document: where s ki is the time derivatives (slope) of the log 2 FC of gene k in sample i. In contrast to Equation (4), Equation (5) was derived without assuming pseudo steady-state, which was necessary to account for the dynamics of gene expressions. The slopes of the log 2 FC at each sampling time point were computed using a second-order accurate finite difference approximation (37) . In summary, the estimation of edge weights in ProTINA involved the following linear regression problem:

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