Method for predicting protein-RNA interaction sites

An interaction site and protein technology, which is applied in the field of prediction of protein-RNA interaction sites with machine learning-related knowledge, can solve problems such as difficulty in meeting prediction requirements, complex experimental techniques, and long experimental periods, and achieve good prediction results. , reduce the training time, the final result is excellent

Inactive Publication Date: 2019-06-28
CENT SOUTH UNIV
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Problems solved by technology

Although these experiments have the advantages of high precision, there are also defects such as long experimental period, high cost, and complicated e

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  • Method for predicting protein-RNA interaction sites
  • Method for predicting protein-RNA interaction sites
  • Method for predicting protein-RNA interaction sites

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Embodiment Construction

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0028] The main process of the present invention is as follows: according to the obtained protein-RNA complex, the effective data with a lower similarity score is obtained; according to the obtained effective data, their sequence-based features, structure-based features, Network features and exposed area features, these features are fused into multidimensional features; sequence features and structural features are calculated based on valid data; ...

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Abstract

The invention discloses a method for predicting protein-RNA interaction sites. Multiple kinds of characteristic data of a protein-RNA compound are combined for forming a complicated multidimensional characteristic set. Then an effective characteristic with high weight is selected through a characteristic selecting algorithm. Finally a protein-RNA interaction site is predicted through a machine learning algorithm. Compared with the prior art, the method is advantageous in that more and more effective characteristics are fused; a more advanced algorithm is used; the more effective characteristics are selected; and besides consideration of prediction of the protein-RNA interaction sites which are proved by experiments, more data can be integrated, such as protein-DNA interaction sides. According to the method of the invention, through fusing more effective algorithm and more characteristic data, the protein-RNA interaction sites can be more accurately predicted than previous technology. Furthermore multiple pairs of protein-RNA interaction sites can be predicted in one time in a large scale manner, thereby effectively settling problems of blindness and high cost of a biological experiment method.

Description

technical field [0001] The invention belongs to the field of bioinformatics, in particular a method for predicting protein-RNA interaction sites by using relevant machine learning knowledge. Background technique [0002] As an important biomacromolecule in living organisms, protein is the basis of all life activities. The focus of the analysis of the mysteries of life lies in the study of protein functions. By identifying various functional sites in proteins, predicting protein functions is one of the main means at present. In organisms, many life processes are closely related to protein-RNA interactions. Obtaining useful information from protein-RNA interaction residues is of great significance for understanding the internal mechanisms and functions of many biological activities related to protein-RNA interactions. [0003] The identification of protein-RNA binding sites is an interesting and challenging problem in computational biology. In the identification of RNA bind...

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Application Information

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IPC IPC(8): G16B20/00
Inventor 魏彦华
Owner CENT SOUTH UNIV
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