Abstract
MSClustering is an efficient software package for visualizing and analyzing complex networks in Cytoscape. Based on the distance matrix of a network that it takes as input, MSClustering automatically displays the minimum span clustering (MSC) of the network at various characteristic levels. To produce a view of the overall network structure, the app then organizes the multi-level results into an MSC tree. Here, we demonstrate the package’s phylogenetic applications in studying the evolutionary relationships of complex systems, including 63 beta coronaviruses and 197 GPCRs. The validity of MSClustering for large systems has been verified by its clustering of 3481 enzymes. Through an experimental comparison, we show that MSClustering outperforms five different state-of-the-art methods in the efficiency and reliability of their clustering.
Original language | English |
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Article number | 14240 |
Journal | International journal of molecular sciences |
Volume | 23 |
Issue number | 22 |
DOIs | |
Publication status | Published - 2022 Nov |
Keywords
- Cytoscape tools
- minimum span clustering
- network visualization
- phylogenetic tree
ASJC Scopus subject areas
- Catalysis
- Molecular Biology
- Spectroscopy
- Computer Science Applications
- Physical and Theoretical Chemistry
- Organic Chemistry
- Inorganic Chemistry