Optimal control method for gene regulation network

A gene regulation network and optimization control technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of occupation, multiple memory, long data processing time, etc.

Active Publication Date: 2017-01-04
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

[0005] At present, when obtaining the optimal control result through the gene regulation ne

Method used

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  • Optimal control method for gene regulation network
  • Optimal control method for gene regulation network
  • Optimal control method for gene regulation network

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specific Embodiment approach

[0112] Then, node x1 in the model can be modeled, where f11 and f12 are candidate Boolean functions corresponding to node x1 in the model, and the probability of each candidate Boolean function being selected is 0.5. The specific implementation is as follows:

[0113] 1) module BN1

[0114] 2) x1:[0..1] init 1;

[0115] 3) d1:[0..1] init 0;

[0116] 4) [csPBN]c=0&s=1&per1=0->0.5:(x1'=f11)&(d1'=0)+0.5:(x1'=f12)&(d1'=1);

[0117] 5) [csPBN]c=0&s=0&per1=0&d1=0->(x1'=f11);

[0118] 6) [csPBN]c=0&s=0&per1=0&d1=1->(x1'=f12);

[0119] 7) [csPBN]c=0&per1=1->(x1'=0);

[0120] 8) [csPBN]c=0&per1=1->(x1'=1);

[0121] 9) endmodule

[0122] The code in line 4 shows that when the transfer switch is turned on and no disturbance event occurs, the value of node x1 depends on f11 with a probability of 0.5 and is marked with d1=0, and the situation after the plus sign is similar; line 5 to The code in line 6 shows that when the transfer switch is closed and the disturbance event does not...

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Abstract

The invention provides an optimal control method for a gene regulation network. The optimal control method comprises the following steps: modeling a PBN (Probabilistic Boolean Network) with interference and context dependent in a probabilistic model detector PRISM to obtain a PRISM-based probabilistic Boolean network model; setting different state return values for a state of the PBN by using a reward structure in the PRISM, wherein the state return values are used for representing a control cost function and terminal cost; determining a first temporal logic formula and a second temporal logic formula respectively for control cost optimization for a limited range and an unlimited range; inputting the PRISM-based probabilistic Boolean network model, the different state return values, the first temporal logic formula and the second temporal logic formula into the probabilistic model detector PRISM to obtain the best optimal control result. The optimal control method, provided by the invention, for the gene regulation network can improve the efficiency for acquiring the best optimal control result under a condition of occupation of relatively low memory capacity.

Description

technical field [0001] The invention relates to the technical field of biological network control, in particular to an optimization control method of a gene regulation network. Background technique [0002] Gene regulatory network is an important biological network, and its modeling and analysis are of great importance for a deeper understanding of biological processes and for the development of effective therapeutic interventions for human diseases. Currently, Boolean networks and probabilistic Boolean networks have been widely used to model gene regulatory networks. Boolean Network (BN) is a simple logical dynamic system proposed by Kauffman in 1969, and is used as an important model to study the dynamic behavior of gene regulatory networks. In a Boolean network, some binary-valued nodes and interaction rules between nodes constitute the topology of the entire network. Assume that the state of the gene is divided into two types: "0" and "1", where "0" represents that the...

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Application Information

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IPC IPC(8): G06F19/00G06N3/00
CPCG06N3/002G16Z99/00
Inventor 魏欧战芸娇郭宗豪
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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