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Maximum grade predication method based on binding Boolean network

A scoring prediction, Boolean network technology, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve problems such as high data quality requirements, high noise in biological data, etc., to achieve accurate network structure and strong robustness Effect

Inactive Publication Date: 2014-03-19
WENZHOU UNIVERSITY
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing prediction method based on the constraint Boolean network - the three rules, it has high requirements on data quality, and it is only suitable for the reasoning of small sample data, and the biological data in the real environment contains more noise, so it is generally only Used as preprocessing for forecasting

Method used

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  • Maximum grade predication method based on binding Boolean network
  • Maximum grade predication method based on binding Boolean network
  • Maximum grade predication method based on binding Boolean network

Examples

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example 1

[0079] Example 1: The gene regulatory network of a budding yeast cell is shown in the attached figure 1 . attached Figure 7 Express data for one of its time series. The three rules and the maximum score prediction method are respectively used to predict the gene regulatory network of the graph, and the results are shown in the attached figure 2 And attached image 3 shown.

[0080] attached figure 2 And attached image 3 The thick solid line in the figure of the three rules in the figure indicates the predicted correct regulatory relationship, the thin dashed line indicates the predicted regulatory relationship that is not fully determined and does not contain the correct one, and the thick dotted line indicates the predicted regulatory relationship that is not fully determined and contains the correct one. The incomplete determination here means that the regulatory relationship between the two genes may not exist or may be one of the positive and negative regulatory ...

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Abstract

The invention relates to a maximum grade predication method based on a binding Boolean network. The maximum grade predication method comprises the following steps that 1, relative mutual information is calculated to determine a candidate predicated gene set; 2, father genes used as target genes are selected from the predicated gene set obtained in the step 1 through the maximum grade predication method. The maximum grade predication method is suitable for predicating the relation of multiple variables based on small-sample data, has stronger robustness on noise, and is more suitable for predicating biological data under a real environment, the predicated network structure is more accurate and detailed, and the right number and the directivity of regulating and control relations and positive and negative regulating and control relations are predicated.

Description

technical field [0001] The invention relates to a method for predicting a gene regulation network, in particular to a method for predicting the maximum score of a gene regulation network by utilizing the constrained Boolean network characteristics. Background technique [0002] An important goal of systems biology research is to describe the molecular mechanisms that regulate specific cellular behaviors and processes. There are many models describing the gene regulation network, for example: Bayesian network and dynamic Bayesian network provide a model that can clarify the dependence relationship between genes; Boolean network and probabilistic Boolean network It is a method for studying the function of a system in terms of state behavior; the differential equation is a continuous model, which can describe the detailed biochemical relationship between genes. These models are uniformly used to study biological phenomena (cell cycle) and diseases (cancer). Therefore, reveali...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 刘文斌欧阳宏嘉方洁沈良忠
Owner WENZHOU UNIVERSITY
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