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Biological Network Motif Recognition Method Based on Backtracking Method and Dynamic Programming Method

A dynamic programming and motif recognition technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of search node displacement space expansion, etc., to prevent omission, improve efficiency, and improve accuracy.

Active Publication Date: 2017-07-11
DALIAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, as the subgraph becomes larger and denser, the displacement space of search nodes will expand rapidly

Method used

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  • Biological Network Motif Recognition Method Based on Backtracking Method and Dynamic Programming Method
  • Biological Network Motif Recognition Method Based on Backtracking Method and Dynamic Programming Method
  • Biological Network Motif Recognition Method Based on Backtracking Method and Dynamic Programming Method

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Embodiment 1

[0037] The embodiments of the present invention are implemented on the premise of the technical solutions of the present invention, and detailed implementation methods and specific operation processes are given, but the protection scope of the present invention is not limited to the following embodiments.

[0038] Step 1: Because the data of the real network is too large, the number of subgraphs has reached as many as one million, and the representation of its association matrix and information matrix is ​​quite complicated, so we first cite a graph with 9 nodes A simple diagram is used as an example diagram (see attached figure 1 ), and then save the information of the graph in a txt file and read it into the program. The content of the txt file is:

[0039] 1 2 1

[0040] 1 5 1

[0041] 2 3 1

[0042] 2 6 1

[0043] 3 1 1

[0044] 3 8 1

[0045] 3 9 1

[0046] 3 9 1

[0047] 4 1 1

[0048] 5 1 1

[0049] 7 2 1

[0050]The first row and the first column are the sta...

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Abstract

The invention relates to the field of biological network motif recognition, in particular to a biological network motif recognition method based on a backtracking method and a dynamic programming method. This method introduces the dynamic programming method into the biological network motif recognition, and makes some improvements to the backtracking method used in the subgraph search process. From the data obtained from the experiment and the comparison results with other methods, this method can more comprehensively search out subgraphs of corresponding scale, so as to identify motifs more accurately; the subgraph search time of this method is also greatly shortened , which shows that this method has good time efficiency.

Description

technical field [0001] The invention relates to a biological network motif recognition method based on the backtracking method and the dynamic programming method. Specifically, the subgraphs of other nodes are searched for by calling the searched subgraphs through the dynamic programming method, and the backtracking is used in the process of searching the subgraphs. A biological network motif recognition method based on the present invention belongs to the field of biological network motif recognition. Background technique [0002] With the completion of the Human Genome Project, we have entered the post-genome era. The main task of bioinformatics in the post-genome era is to explore all the particles in a living cell and the relationship between these particles, which constitute a complex biological network. In recent years, researchers have focused on studying these complex biological networks. Network motifs have been demonstrated as fundamental functional units in thes...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/18
Inventor 张强宋晓利周昌军王宾
Owner DALIAN UNIV