Multi-target phylogenetic tree construction method based on feature hierarchy

A multi-objective system and construction method technology, applied in the field of multi-objective phylogenetic tree construction based on the feature level, can solve problems such as conflicts, and achieve the effect of avoiding limitations

Active Publication Date: 2020-07-28
NORTHWEST UNIV(CN)
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the results of multiple phylogenetic inferences may be conflicting or consistent
When goals conflict, there is often no way to satisfy all goals

Method used

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  • Multi-target phylogenetic tree construction method based on feature hierarchy
  • Multi-target phylogenetic tree construction method based on feature hierarchy
  • Multi-target phylogenetic tree construction method based on feature hierarchy

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Embodiment Construction

[0059] like Figure 1 to Figure 11 As shown, this embodiment provides a multi-objective phylogenetic tree construction method based on feature hierarchy, and the detailed steps are as follows:

[0060] Step 1: Construct and formally express the hierarchical relationship of features

[0061] Step 1.1: Combining prior knowledge and corresponding feature descriptions, discover the dependencies between features, determine the main features, subordinate features, and the logical constraints between the values ​​of the main features and subordinate features. For a clearer understanding, take figure 2 Take this as an example. According to the feature description, it can be seen that the values ​​of the feature "tail" include "absence (0)" and "existence (1)"; the values ​​of the feature "tail color" include "blue (0)" and "red ( 1)" and "not applicable (-)", if and only if the value of the feature "tail" is "absent (0)", the value of "tail color" is "not applicable (-)"; the feat...

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Abstract

The invention discloses a multi-target phylogenetic tree construction method based on feature hierarchy. The method comprises the steps: generating a corresponding feature hierarchy relation by combining with the feature description of form data, and estimating a missing value by combining with the dependence relation between features to obtain a complete data set; and by combining with a maximumreduction principle and a maximum likelihood principle based on an inapplicable Fitch algorithm, carrying out parallel multi-target phylogenetic tree construction, so that problems caused by inapplicable data be well measured, and the limitation of tree construction under a single principle is avoided. Compared with a traditional phylogenetic analysis method, the method of the invention has the advantages that the problem of tree structure uncertainty caused by missing data and inapplicable data can be well solved, and a basis is provided for biologists to research species evolution through various tree building principles.

Description

technical field [0001] The invention belongs to the field of biological information, and relates to the analysis and construction of a developmental tree in phylogenetic research, in particular to a method for constructing a multi-objective phylogenetic tree based on feature levels. Background technique [0002] Phylogenetics is the study of evolutionary relationships, such as the evolutionary history and relationships between species or populations, to understand when and likely speciation events occurred, and thus to study the origin of species. The phylogenetic analysis is to infer and evaluate these evolutionary relationships, and its purpose is to find a phylogenetic tree that conforms to the evolution of species. For a clearer understanding of the purpose of the study, the figure 1 It can be seen that by sorting out the morphological data of the collected fossils, the species characteristic matrix can be obtained; through the phylogenetic analysis of the morphological...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B5/00G06N3/12
CPCG16B5/00G06N3/126
Inventor 冯筠刘泽云刘蒙侯刚冯宏伟
Owner NORTHWEST UNIV(CN)
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