Graph Theory
Markov clustering is an algorithm designed to discover clusters in a graph by simulating random walks. It operates on the principle of flow simulation, where the goal is to maximize the flow within clusters while minimizing the flow between them. This technique is particularly useful in analyzing biological networks, as it can help identify functional groups or modules within complex biological systems.
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