Applications of cuckoo search and ant lion optimization for analyzing protein-protein interaction through regularized Markov clustering on coronavirus

2021 ◽  
Vol 1722 ◽  
pp. 012008
Author(s):  
A Rizki ◽  
A Bustamam ◽  
D Sarwinda
Keyword(s):  
Protein Interaction ◽  
Cuckoo Search ◽  
Protein Protein Interaction ◽  
Ant Lion Optimization ◽  
Markov Clustering ◽  
Ant Lion

Using a Genetic Algorithm and Markov Clustering on Protein–Protein Interaction Graphs

2012 ◽  
Vol 1 (2) ◽  
pp. 35-47
Author(s):  
Charalampos Moschopoulos ◽  
Grigorios Beligiannis ◽  
Spiridon Likothanassis ◽  
Sophia Kossida
Keyword(s):  
Genetic Algorithm ◽  
Protein Interaction ◽  
Clustering Algorithm ◽  
Protein Complexes ◽  
Clustering Algorithms ◽  
Interaction Graphs ◽  
Protein Protein Interaction ◽  
Protein Complex Detection ◽  
Successful Prediction ◽  
Markov Clustering

In this paper, a Genetic Algorithm is applied on the filter of the Enhanced Markov Clustering algorithm to optimize the selection of clusters having a high probability to represent protein complexes. The filter was applied on the results (obtained by experiments made on five different yeast datasets) of three different algorithms known for their efficiency on protein complex detection through protein interaction graphs. The results are compared with three popular clustering algorithms, proving the efficiency of the proposed method according to metrics such as successful prediction rate and geometrical accuracy.

Using a Genetic Algorithm and Markov Clustering on Protein–Protein Interaction Graphs

2013 ◽  
pp. 805-816
Author(s):  
Charalampos Moschopoulos ◽  
Grigorios Beligiannis ◽  
Spiridon Likothanassis ◽  
Sophia Kossida
Keyword(s):  
Genetic Algorithm ◽  
Protein Interaction ◽  
Clustering Algorithm ◽  
Protein Complexes ◽  
Clustering Algorithms ◽  
Interaction Graphs ◽  
Protein Protein Interaction ◽  
Protein Complex Detection ◽  
Markov Clustering ◽  
Complex Detection

In this paper, a Genetic Algorithm is applied on the filter of the Enhanced Markov Clustering algorithm to optimize the selection of clusters having a high probability to represent protein complexes. The filter was applied on the results (obtained by experiments made on five different yeast datasets) of three different algorithms known for their efficiency on protein complex detection through protein interaction graphs. The results are compared with three popular clustering algorithms, proving the efficiency of the proposed method according to metrics such as successful prediction rate and geometrical accuracy.

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