Key protein identification method based on Markov random walk
A random walk and identification method technology, applied in the field of bioinformatics, can solve problems such as false positives in protein interaction data, neglect of protein biological characteristics, and noise in PPI networks, so as to expand the application range and practicability, and overcome data noise High, efficiency-enhancing effect
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[0076] To verify the performance of the proposed algorithm EPM in this chapter, we compared the number of key proteins identified with other five methods (DC, BC, LAC, PeC and CoEWC). For each method, we select the protein recognition results of top100, top200, top300, top400, top500, and top600 as candidate sets, and then intersect the proteins in each candidate set with the standard key protein set to obtain the real key in the candidate set The amount of protein, the experimental results are shown in Figure 2.
[0077] from Figure 2a , 2b , 2c, 2d, 2e, and 2f, it can be seen that in the yeast PPI network, the algorithm EPM proposed by us can achieve better results than other methods in identifying key proteins. When the top500 and top600 key proteins are used as candidate sets, the number of proteins identified by the algorithm proposed in this chapter is significantly higher than other methods. Among them, compared with the PeC method, when extracting the top100, top20...
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