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ode15s  (MathWorks Inc)


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    MathWorks Inc ode15s
    I) The repressilator ( A ) Topology of the repressilator. ( B ) Topology of the circuit in the interface generated by the make_graph() method: the red dots N 1 , N 2 , and N 3 represent the nodes in the circuit. The red arrows denote the directed edges of the graph, illustrating the repression interactions between nodes. Additionally, the yellow dots N 1 ∣ − N 3 , N 2 ∣ − N 1 , and N 3 ∣ − N 2 represent the regulatory interactions. For example, N 1 ∣ − N 3 denotes that node N 1 is repressed by N 3 . ( C ) Deterministic and ( D ) stochastic simulations of the repressilator using the Elowitz model, as described in Appendix Table in the . The detailed information about the model is available in the file “repressilator.html“ode15s” solver of MATLAB, while the stochastic simulations were performed using the “adaptivesa” solver of COPASI in every case. " width="250" height="auto" />
    Ode15s, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 97/100, based on 545 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/ode15s/product/MathWorks Inc
    Average 97 stars, based on 545 article reviews
    ode15s - by Bioz Stars, 2026-04
    97/100 stars

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    1) Product Images from "A tool for modeling gene regulatory networks (GRN_modeler) and its applications to synthetic biology"

    Article Title: A tool for modeling gene regulatory networks (GRN_modeler) and its applications to synthetic biology

    Journal: Molecular Systems Biology

    doi: 10.1038/s44320-025-00148-8

    I) The repressilator ( A ) Topology of the repressilator. ( B ) Topology of the circuit in the interface generated by the make_graph() method: the red dots N 1 , N 2 , and N 3 represent the nodes in the circuit. The red arrows denote the directed edges of the graph, illustrating the repression interactions between nodes. Additionally, the yellow dots N 1 ∣ − N 3 , N 2 ∣ − N 1 , and N 3 ∣ − N 2 represent the regulatory interactions. For example, N 1 ∣ − N 3 denotes that node N 1 is repressed by N 3 . ( C ) Deterministic and ( D ) stochastic simulations of the repressilator using the Elowitz model, as described in Appendix Table in the . The detailed information about the model is available in the file “repressilator.html
    Figure Legend Snippet: I) The repressilator ( A ) Topology of the repressilator. ( B ) Topology of the circuit in the interface generated by the make_graph() method: the red dots N 1 , N 2 , and N 3 represent the nodes in the circuit. The red arrows denote the directed edges of the graph, illustrating the repression interactions between nodes. Additionally, the yellow dots N 1 ∣ − N 3 , N 2 ∣ − N 1 , and N 3 ∣ − N 2 represent the regulatory interactions. For example, N 1 ∣ − N 3 denotes that node N 1 is repressed by N 3 . ( C ) Deterministic and ( D ) stochastic simulations of the repressilator using the Elowitz model, as described in Appendix Table in the . The detailed information about the model is available in the file “repressilator.html". II) Redesigned repressilator for an independent modulation of amplitude and frequency. ( A ) Topology of the redesigned repressilator. “C" and “L" are proteases, “I 1 " and “I 2 " external inducers, “U" and “Y" transcription factors activating N 4 and N 2 , respectively. The dotted gray lines indicate which proteins are degraded by the proteases. ( B ) Topology of the circuit in the interface. ( C ) The effect of the inducers on the amplitude of N 4 . ( D ) The effect of the inducers on the time period of N 4 . The detailed information about the model is available in the file “Tomazou.html". III) The CRISPRlator circuit. ( A ) Topology of the CRISPRlator. ( B ) Topology of the circuit in the interface. For example, N 1 NOHILL∣-N 3 denotes that node N 1 is repressed by N 3 through an input named NOHILL, which corresponds to the CRISPRi interaction in the node model. This repression is incorporated into the system by introducing new reactions (R 6 and R 7 in Appendix Table ), where the dCas:sgRNA N3 complex binds to DNA N1 , inhibiting transcription at node N 1 . ( C ) Deterministic and ( D ) stochastic simulations of the CRISPRlator generated by the model detailed in Appendix Table in the . The detailed information about the model is available in the file “CRISPR.html”. The deterministic simulations were fulfilled with the “ode15s” solver of MATLAB, while the stochastic simulations were performed using the “adaptivesa” solver of COPASI in every case.

    Techniques Used: Generated, CRISPR



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    I) The repressilator ( A ) Topology of the repressilator. ( B ) Topology of the circuit in the interface generated by the make_graph() method: the red dots N 1 , N 2 , and N 3 represent the nodes in the circuit. The red arrows denote the directed edges of the graph, illustrating the repression interactions between nodes. Additionally, the yellow dots N 1 ∣ − N 3 , N 2 ∣ − N 1 , and N 3 ∣ − N 2 represent the regulatory interactions. For example, N 1 ∣ − N 3 denotes that node N 1 is repressed by N 3 . ( C ) Deterministic and ( D ) stochastic simulations of the repressilator using the Elowitz model, as described in Appendix Table in the . The detailed information about the model is available in the file “repressilator.html“ode15s” solver of MATLAB, while the stochastic simulations were performed using the “adaptivesa” solver of COPASI in every case. " width="250" height="auto" />
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    I) The repressilator ( A ) Topology of the repressilator. ( B ) Topology of the circuit in the interface generated by the make_graph() method: the red dots N 1 , N 2 , and N 3 represent the nodes in the circuit. The red arrows denote the directed edges of the graph, illustrating the repression interactions between nodes. Additionally, the yellow dots N 1 ∣ − N 3 , N 2 ∣ − N 1 , and N 3 ∣ − N 2 represent the regulatory interactions. For example, N 1 ∣ − N 3 denotes that node N 1 is repressed by N 3 . ( C ) Deterministic and ( D ) stochastic simulations of the repressilator using the Elowitz model, as described in Appendix Table in the . The detailed information about the model is available in the file “repressilator.html“ode15s” solver of MATLAB, while the stochastic simulations were performed using the “adaptivesa” solver of COPASI in every case. " width="250" height="auto" />
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    I) The repressilator ( A ) Topology of the repressilator. ( B ) Topology of the circuit in the interface generated by the make_graph() method: the red dots N 1 , N 2 , and N 3 represent the nodes in the circuit. The red arrows denote the directed edges of the graph, illustrating the repression interactions between nodes. Additionally, the yellow dots N 1 ∣ − N 3 , N 2 ∣ − N 1 , and N 3 ∣ − N 2 represent the regulatory interactions. For example, N 1 ∣ − N 3 denotes that node N 1 is repressed by N 3 . ( C ) Deterministic and ( D ) stochastic simulations of the repressilator using the Elowitz model, as described in Appendix Table in the . The detailed information about the model is available in the file “repressilator.html“ode15s” solver of MATLAB, while the stochastic simulations were performed using the “adaptivesa” solver of COPASI in every case. " width="250" height="auto" />
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    I) The repressilator ( A ) Topology of the repressilator. ( B ) Topology of the circuit in the interface generated by the make_graph() method: the red dots N 1 , N 2 , and N 3 represent the nodes in the circuit. The red arrows denote the directed edges of the graph, illustrating the repression interactions between nodes. Additionally, the yellow dots N 1 ∣ − N 3 , N 2 ∣ − N 1 , and N 3 ∣ − N 2 represent the regulatory interactions. For example, N 1 ∣ − N 3 denotes that node N 1 is repressed by N 3 . ( C ) Deterministic and ( D ) stochastic simulations of the repressilator using the Elowitz model, as described in Appendix Table in the . The detailed information about the model is available in the file “repressilator.html“ode15s” solver of MATLAB, while the stochastic simulations were performed using the “adaptivesa” solver of COPASI in every case. " width="250" height="auto" />
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    I) The repressilator ( A ) Topology of the repressilator. ( B ) Topology of the circuit in the interface generated by the make_graph() method: the red dots N 1 , N 2 , and N 3 represent the nodes in the circuit. The red arrows denote the directed edges of the graph, illustrating the repression interactions between nodes. Additionally, the yellow dots N 1 ∣ − N 3 , N 2 ∣ − N 1 , and N 3 ∣ − N 2 represent the regulatory interactions. For example, N 1 ∣ − N 3 denotes that node N 1 is repressed by N 3 . ( C ) Deterministic and ( D ) stochastic simulations of the repressilator using the Elowitz model, as described in Appendix Table in the . The detailed information about the model is available in the file “repressilator.html“ode15s” solver of MATLAB, while the stochastic simulations were performed using the “adaptivesa” solver of COPASI in every case. " width="250" height="auto" />
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    Image Search Results


    I) The repressilator ( A ) Topology of the repressilator. ( B ) Topology of the circuit in the interface generated by the make_graph() method: the red dots N 1 , N 2 , and N 3 represent the nodes in the circuit. The red arrows denote the directed edges of the graph, illustrating the repression interactions between nodes. Additionally, the yellow dots N 1 ∣ − N 3 , N 2 ∣ − N 1 , and N 3 ∣ − N 2 represent the regulatory interactions. For example, N 1 ∣ − N 3 denotes that node N 1 is repressed by N 3 . ( C ) Deterministic and ( D ) stochastic simulations of the repressilator using the Elowitz model, as described in Appendix Table in the . The detailed information about the model is available in the file “repressilator.html

    Journal: Molecular Systems Biology

    Article Title: A tool for modeling gene regulatory networks (GRN_modeler) and its applications to synthetic biology

    doi: 10.1038/s44320-025-00148-8

    Figure Lengend Snippet: I) The repressilator ( A ) Topology of the repressilator. ( B ) Topology of the circuit in the interface generated by the make_graph() method: the red dots N 1 , N 2 , and N 3 represent the nodes in the circuit. The red arrows denote the directed edges of the graph, illustrating the repression interactions between nodes. Additionally, the yellow dots N 1 ∣ − N 3 , N 2 ∣ − N 1 , and N 3 ∣ − N 2 represent the regulatory interactions. For example, N 1 ∣ − N 3 denotes that node N 1 is repressed by N 3 . ( C ) Deterministic and ( D ) stochastic simulations of the repressilator using the Elowitz model, as described in Appendix Table in the . The detailed information about the model is available in the file “repressilator.html". II) Redesigned repressilator for an independent modulation of amplitude and frequency. ( A ) Topology of the redesigned repressilator. “C" and “L" are proteases, “I 1 " and “I 2 " external inducers, “U" and “Y" transcription factors activating N 4 and N 2 , respectively. The dotted gray lines indicate which proteins are degraded by the proteases. ( B ) Topology of the circuit in the interface. ( C ) The effect of the inducers on the amplitude of N 4 . ( D ) The effect of the inducers on the time period of N 4 . The detailed information about the model is available in the file “Tomazou.html". III) The CRISPRlator circuit. ( A ) Topology of the CRISPRlator. ( B ) Topology of the circuit in the interface. For example, N 1 NOHILL∣-N 3 denotes that node N 1 is repressed by N 3 through an input named NOHILL, which corresponds to the CRISPRi interaction in the node model. This repression is incorporated into the system by introducing new reactions (R 6 and R 7 in Appendix Table ), where the dCas:sgRNA N3 complex binds to DNA N1 , inhibiting transcription at node N 1 . ( C ) Deterministic and ( D ) stochastic simulations of the CRISPRlator generated by the model detailed in Appendix Table in the . The detailed information about the model is available in the file “CRISPR.html”. The deterministic simulations were fulfilled with the “ode15s” solver of MATLAB, while the stochastic simulations were performed using the “adaptivesa” solver of COPASI in every case.

    Article Snippet: We conducted deterministic simulations using MATLAB’s ode15s and sundials solvers with the SimBiology toolbox.

    Techniques: Generated, CRISPR