A method for identifying key proteins using an improved hits algorithm
A protein, a key technology, applied in the field of bioinformatics, can solve the problems of not considering the directionality of the weighting process, the recognition accuracy and efficiency are not very high, and the lack of holistic understanding of the method, so as to achieve a good fusion of network topology characteristics and biological characteristics, Promoting widespread application and improving operational efficiency
Active Publication Date: 2022-08-05
SHAANXI NORMAL UNIV
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[0005] Although the above-mentioned researchers have proposed a large number of methods to identify key proteins, the recognition accuracy and efficiency are still not very high, and most of the methods need to analyze the influence of parameters on the method, lack of overall understanding of the method, and most of the The method is to convert the PPI network into an undirected graph, without considering the directionality in the weighting process
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[0118] This example intends to use the yeast data set of the DIP database as the simulation data set. After deduplication and other processing, the yeast data set in the DIP contains 5093 proteins and 24743 interaction relationships. Gene expression data were collected from the yeast dataset in the GEO database, which included 7074 genes. The GO database is one of the most comprehensive ontology databases in bioinformatics, and yeast GO annotation data was obtained from the GO Consortium database. The subcellular locations were divided into eleven locations and the data was taken from the COMPARTMENTS database which contained 5095 proteins and 206831 subcellular location records. The key protein standard database is integrated from 4 databases, including MIPS, SGD, DEG and SGDP, which contain 1285 key proteins, corresponding to 1167 key proteins in yeast data. The experimental platform of the present invention is Windows 10 64-bit operating system, the processor is Intel(R) C...
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The invention translates protein interaction network into pre -processing of the edge of the direction diagram, the edge of the network of protein interaction, the webbage edge of the network topology, the addition of the network biological characteristics, and the use of the HITS algorithmValue and central values are processed, the comprehensive score of each node is obtained, and key proteins are generated.The present invention verifies the identification effect of the present invention through simulation experiments. The experimental results use indicators of sensitivity, specificity, positive prediction value, negative prediction value, accuracy and recall rate, accurate value and other indicators to evaluate the method of the present invention.; And compare the invention with other methods of identifying key proteins, and the results show that the invention uses a improved HITS algorithm to identify key protein methods has good performance. From the above evaluation indicators, the present invention is better than other methods.
Description
technical field [0001] The invention belongs to the technical field of biological information, relates to a method for identifying key proteins in a protein interaction network, and in particular relates to a method for identifying key proteins by using an improved HITS algorithm. Background technique [0002] It is well known that proteins are major components of cellular physiological metabolic pathways important to organisms. Proteins are involved in various biological processes and perform almost all cellular functions by interacting with other proteins or DNA. With the development of proteomics in the post-genomic era, some protein-related topics have become hot topics, including the discovery of protein structure and function, the identification of key proteins or protein complexes, and functional modules. Remarkably, removing just one of these key proteins can lead to fatal defects in living organisms. In addition, some recent findings suggest that key proteins are ...
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IPC IPC(8): G16B20/00
Inventor 雷秀娟王思果赵杰
Owner SHAANXI NORMAL UNIV