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A Maximum Score Prediction Method Based on Constrained Boolean Networks

A Boolean network, score prediction technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of high data quality requirements, biological data noise, etc.

Inactive Publication Date: 2016-07-06
WENZHOU UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

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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

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  • A Maximum Score Prediction Method Based on Constrained Boolean Networks
  • A Maximum Score Prediction Method Based on Constrained Boolean Networks
  • A Maximum Score Prediction Method Based on Constrained Boolean Networks

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Embodiment Construction

[0046] A kind of maximum scoring prediction method based on the constraint Boolean network of the present invention, comprises the following steps:

[0047] The first step is to calculate the relative mutual information to determine the candidate prediction gene set,

[0048] ① Define an M matrix, and calculate the relative mutual information between two variables according to the following formula

[0049] θ i j = M I ( x j t + 1 , x i t + 1 ) m i ...

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Abstract

The invention relates to a maximum score prediction method based on a constrained Boolean network, comprising the following steps: the first step is to calculate the relative mutual information to determine the candidate prediction gene set; the second step is to obtain the maximum score prediction method from the first step Select the parent gene as the target gene in the predicted gene set. The present invention is suitable for predicting the relationship between multiple variables based on small sample data. The present invention is more robust to noise and more suitable for biological For the prediction of data, the network structure of the invention prediction is more accurate and detailed, which is reflected in the correct number of predicted regulatory relationships, the directionality of regulatory relationships, and positive and negative regulatory relationships.

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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Patent Type & Authority Patents(China)
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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