Download PDF by G. Rosolini (auth.), David H. Pitt, Axel Poigné, David E.: Category Theory and Computer Science: Edinburgh, U.K.,

By G. Rosolini (auth.), David H. Pitt, Axel Poigné, David E. Rydeheard (eds.)

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Read or Download Category Theory and Computer Science: Edinburgh, U.K., September 7–9, 1987 Proceedings PDF

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Percolation on finite graphs and isoperimetric inequalities. Annals of Probability 32(3), 1727–1745 (2004) 2. : Largest random component of a k-cube. Combinatorica 2, 1–7 (1982) 3. : The evolution of random subgraphs of the cube. Random Structures and Algorithms 3(1), 55–90 (1992) 4. : Percolation on dense graph sequences (preprint) 5. : Random subgraphs of finite graphs. I. The scaling window under the triangle condition. Random Structures and Algorithms 27(2), 137–184 (2005) 6. : Random subgraphs of finite graphs.

Algorithm 6. (Algorithm for counting 4-cliques that are adjacent to v) 1. Cl(v) = 0. 2. For every vertex u ∈ N (v): Approximating the Number of Network Motifs 23 (a) Compute N (v) ∩ N (u): i. Go over all the vertices in the adjacency list of v and the adjacency list of u, and add each vertex to a list. (Thus a vertex can appear several times in the list). ii. Sort the vertices in the list (which is a multiset) according the names of the vertices. iii. For each vertex in the list count the number of times it appears in the list.

Waterman, M. ) RECOMB 2005. LNCS (LNBI), vol. 3500, pp. 1–13. Springer, Heidelberg (2005) 16. : QPath: a method for querying pathways in a protein-protein interaction network. Bioinformatics 7, 199 (2006) 17. : Efficient detection of network motifs. com Abstract. We consider the problem of finding dense subgraphs with specified upper or lower bounds on the number of vertices. We introduce two optimization problems: the densest at-least-k-subgraph problem (dalks), which is to find an induced subgraph of highest average degree among all subgraphs with at least k vertices, and the densest at-most-k-subgraph problem (damks), which is defined similarly.

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