Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Calculating method of restrictive boolean network degeneracy

A Boolean network, computing method technology, applied in computing, special data processing applications, instruments, etc., to solve problems such as system paralysis or degradation

Active Publication Date: 2015-05-06
PEOPLES LIBERATION ARMY ORDNANCE ENG COLLEGE
View PDF2 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, some nerve cells in the brain are apoptotic every day, and the olfactory cells of dogs are all replaced every month, but their physiological functions are still normal. paralyzed or degraded

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Calculating method of restrictive boolean network degeneracy
  • Calculating method of restrictive boolean network degeneracy
  • Calculating method of restrictive boolean network degeneracy

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050] Embodiment 1, a formula for calculating the degeneracy of a suppressed Boolean network.

[0051] The main idea of ​​the degeneracy measurement of the suppressed Boolean network is to measure the overlapping amount of the contribution of all node sets to the overall function of the suppressed Boolean network (or called the overlapping amount of functional contribution).

[0052] The suppressive Boolean network includes an input layer, a transduction layer and an output layer, and it is assumed that the input layer has l nodes, the transduction layer has m nodes, and the output layer has t nodes. The m nodes in the transduction layer are grouped and divided into collections (or node collections), k is the collection size, representing the number of nodes contained in a collection, 1≤k≤m; the divided collections are grouped according to the collection scale, that is, those with the same number of nodes Sets are grouped into one group, and the grouping with a set size of ...

Embodiment 2

[0059] Embodiment 2, a method for calculating the degeneracy of a suppressed Boolean network.

[0060] The calculation method of the suppressed Boolean network degeneracy provided by the present invention comprises the following steps:

[0061] The first step is to clarify the inhibitory Boolean network (such as figure 1 shown), calculate the truth table of the target function of the inhibitory Boolean network.

[0062] Such as figure 1 As shown, the suppressive Boolean network is recorded as a vector F=(V, W), V represents the set of all nodes in the network, and W represents the weight matrix of the regulatory relationship between nodes. The suppressive Boolean network is divided into an input layer 10 , a transduction layer 11 and an output layer 12 . In the biological network, the input layer 10 nodes represent signal perception receptors on the cell surface, which are used to sense external environmental stimuli; the transduction layer 11 nodes represent signal transdu...

Embodiment 3

[0085] Embodiment 3, a method for calculating the degeneracy of a suppressed Boolean network.

[0086] A suppressive Boolean network is known. The input layer has l=2 nodes, the transduction layer has m=7 nodes, and the output layer has t=3 nodes. The network topology is as follows Figure 5 shown.

[0087] The first step, calculate according to formula (3) in embodiment 2 Figure 5 The state value of each node in the suppressed Boolean network shown is obtained, Figure 5 See Table 2 for the truth table of the target function of the suppressed Boolean network shown.

[0088] Table 2: Figure 5 The truth table of the target function for all nodes

[0089]

[0090]

[0091] step two, yes Figure 5 In the suppressed Boolean network shown, the transduction layer nodes are divided into sets, and all the divided sets are grouped according to the set size.

[0092] Figure 5 The transduction layer of the suppressed Boolean network shown has 7 nodes (node ​​numbers are 1...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a calculating method of restrictive boolean network degeneracy. The calculating method of the restrictive boolean network degeneracy comprises the following steps of carrying out set partitioning on all nodes in a transduction layer, grouping partitioned sets; in each group, calculating function contribution overlap amount, as shown in the figure, between each set and a complementary set thereof, and averaging to obtain a mean as shown in the figure; summing the function contribution overlap amount mean of each group, wherein the obtained result is the degeneracy of a restrictive boolean network. The calculation formula of the restrictive boolean network degeneracy is shown in the figure. According to the calculating method of the restrictive boolean network degeneracy provided by the invention, knowledge on biology degeneracy is step up to quantitative depiction from qualitative description, and a degeneracy phenomenon in a complex biological network can be cognized accurately and conveniently.

Description

technical field [0001] The invention relates to a method for calculating degeneracy, in particular to a method for calculating degeneracy of suppressed Boolean networks. Background technique [0002] The rapid progress of microelectronics technology has greatly improved the level of integration, intelligence and precision of electronic equipment, making it play an increasingly important role in the fields of communication, transportation, finance and military. However, an increasing number of electronic devices will also intentionally or unintentionally emit high-density, high-field-strength, wide-spectrum electromagnetic waves, coupled with natural strong electromagnetic sources such as lightning electromagnetic pulses, electrostatic discharge electromagnetic pulses, nuclear electromagnetic pulses, high-power microwaves, Man-made strong electromagnetic sources such as ultra-broadband have made the space electromagnetic environment increasingly complex and harsh. Despite th...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 满梦华马贵蕾张娅褚杰
Owner PEOPLES LIBERATION ARMY ORDNANCE ENG COLLEGE
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com