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...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| منشور في: |
2025
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| الموضوعات: | |
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إضافة وسم
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| 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> |
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