Perturbations and their effects within networks.

<p><b>(A)</b> Overview of gene expression model and its parameters. Here, <i>σ</i> is the logistic sigmoid . <b>(B)</b> Example forward simulation of the dynamical systems model. Trace lines show genes, whose expression values are initialized at zero. The sy...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Matthew Aguirre (9558032) (author)
مؤلفون آخرون: Jeffrey P. Spence (15317543) (author), Guy Sella (230321) (author), Jonathan K. Pritchard (8027465) (author)
منشور في: 2025
الموضوعات:
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الوصف
الملخص:<p><b>(A)</b> Overview of gene expression model and its parameters. Here, <i>σ</i> is the logistic sigmoid . <b>(B)</b> Example forward simulation of the dynamical systems model. Trace lines show genes, whose expression values are initialized at zero. The system eventually reaches a steady-state, and is then subject to perturbation (knockout of gene <i>j</i>, i.e. holding <i>x</i><sub><i>j</i></sub> = 0). Further forward simulation leads to a new steady-state, from which we can compute perturbation effects ( for other genes <i>i</i>). <b>(C)</b> Distribution of knockout (KO) effects (i.e., fold-changes in expression <i>x</i><sub><i>i</i></sub> of a focal gene <i>i</i>) in 50 example GRNs, along with the median distribution (black line). <b>(D)</b> KO effects as a function of network distance between two genes, and <b>(E)</b> within and across modules given by the generating algorithm. Note that the solid lines in <b>(D)</b> and <b>(E)</b> are the median distributions over the 50 example GRNs, split respectively by distances and modules.</p>