TY - GEN

T1 - Deterministic parameterized algorithms for the graph motif problem

AU - Pinter, Ron Y.

AU - Shachnai, Hadas

AU - Zehavi, Meirav

PY - 2014/1/1

Y1 - 2014/1/1

N2 - We study the classic Graph Motif problem: given a graph G=(V,E) with a set of colors for each node, and a multiset M of colors, we seek a subtree T⊆G, and a coloring of the nodes in T, such that T carries exactly (also with respect to multiplicity) the colors in M. Graph Motif plays a central role in the study of pattern matching problems, primarily motivated from the analysis of complex biological networks. Previous algorithms for Graph Motif and its variants either rely on techniques for developing randomized algorithms that, if derandomized, render them inefficient, or the algebraic narrow sieves technique for which there is no known derandomization. In this paper, we present fast deterministic parameterized algorithms for Graph Motif and its variants. Specifically, we give such an algorithm for the more general Graph Motif with Deletions problem, followed by faster algorithms for Graph Motif and other well-studied special cases. Our algorithms make non-trivial use of representative families, and a novel tool that we call guiding trees, together enabling the efficient construction of the output tree.

AB - We study the classic Graph Motif problem: given a graph G=(V,E) with a set of colors for each node, and a multiset M of colors, we seek a subtree T⊆G, and a coloring of the nodes in T, such that T carries exactly (also with respect to multiplicity) the colors in M. Graph Motif plays a central role in the study of pattern matching problems, primarily motivated from the analysis of complex biological networks. Previous algorithms for Graph Motif and its variants either rely on techniques for developing randomized algorithms that, if derandomized, render them inefficient, or the algebraic narrow sieves technique for which there is no known derandomization. In this paper, we present fast deterministic parameterized algorithms for Graph Motif and its variants. Specifically, we give such an algorithm for the more general Graph Motif with Deletions problem, followed by faster algorithms for Graph Motif and other well-studied special cases. Our algorithms make non-trivial use of representative families, and a novel tool that we call guiding trees, together enabling the efficient construction of the output tree.

UR - http://www.scopus.com/inward/record.url?scp=84906261085&partnerID=8YFLogxK

U2 - 10.1007/978-3-662-44465-8_50

DO - 10.1007/978-3-662-44465-8_50

M3 - Conference contribution

AN - SCOPUS:84906261085

SN - 9783662444641

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 589

EP - 600

BT - Mathematical Foundations of Computer Science 2014 - 39th International Symposium, MFCS 2014, Proceedings

PB - Springer Verlag

T2 - 39th International Symposium on Mathematical Foundations of Computer Science, MFCS 2014

Y2 - 25 August 2014 through 29 August 2014

ER -