This paper presents a linear-time delay algorithm for enumerating all directed acyclic subgraphs of a directed graph G(V,E) that have their sources and targets included in two subsets S and T of V, respectively. From these subgraphs, called pitches, the maximal ones, called stories, may be extracted in a dramatically more efficient way in relation to a previous story telling algorithm. The improvement may even increase if a pruning technique is further applied that avoids generating many pitches which have no chance to lead to a story. We experimentally demonstrate these statements by making use of a quite large dataset of real metabolic pathways and networks.

Telling Stories Fast / M. Borassi;P. Crescenzi;V. Lacroix;A. Marino;M.-F. Sagot;P. Vieira Milreu. - STAMPA. - 7933:(2013), pp. 200-211. (Intervento presentato al convegno 12th International Symposium on Experimental Algorithms) [10.1007/978-3-642-38527-8_19].

Telling Stories Fast

CRESCENZI, PIERLUIGI;MARINO, ANDREA;
2013

Abstract

This paper presents a linear-time delay algorithm for enumerating all directed acyclic subgraphs of a directed graph G(V,E) that have their sources and targets included in two subsets S and T of V, respectively. From these subgraphs, called pitches, the maximal ones, called stories, may be extracted in a dramatically more efficient way in relation to a previous story telling algorithm. The improvement may even increase if a pruning technique is further applied that avoids generating many pitches which have no chance to lead to a story. We experimentally demonstrate these statements by making use of a quite large dataset of real metabolic pathways and networks.
2013
Lecture Notes in Computer Science: Experimental Algorithms
12th International Symposium on Experimental Algorithms
M. Borassi;P. Crescenzi;V. Lacroix;A. Marino;M.-F. Sagot;P. Vieira Milreu
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/879371
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