evolmod - Inferring How Networks Evolved 858L Inferring...

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Unformatted text preview: Inferring How Networks Evolved 858L Inferring network mechanisms: The Drosophila melanogaster protein interaction network Manuel Middendorf, Etay Ziv, and Chris H. Wiggins RDS - Random Static Erdos-Renyi (1960): Create n vertices Between every pair of vertices {u,v}, add an edge with probability p . ShowGraphArray[Partition[Table[RandomGraph[15, p], {p, 0.1, 0.9, 0.1}], 3]] Expected degree is ( n-1) p RDG - Random Growing G i-1 u i Parameters: n = number of nodes; M = expected # of edges. At time i , a node is added. Then M/n edges are added uniformly at random. Added edges might not involve u i . Nodes added earlier have more chances to be adjacent to edges. LPA Linear Preferential Attachment u 1 u 2 u 3 u 4 u i-2 u i-1 u i Histogram: degree( u j ) + a , normalized to be a probability distribution: Parameters: n = number of nodes; M = number of edges; a = smoothing parameter. At time i , a node u i is added. M/ n edges are added between u i and the existing nodes drawn randomly according to the histogram. AGV Aging Vertices A V i-1 u i For each potential edge: With probability , add the edge....
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This note was uploaded on 01/13/2012 for the course CMSC 423 taught by Professor Staff during the Fall '07 term at Maryland.

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evolmod - Inferring How Networks Evolved 858L Inferring...

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