Alignment of metabolic pathways

Pinter, Ron Y.; Rokhlenko, Oleg; Yeger-Lotem, Esti; Ziv-Ukelson, Michal

doi:10.1093/bioinformatics/bti554

Cited by 182 publications

(153 citation statements)

References 16 publications

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“…Each of these subgraphs is mapped to the graph it resembles in P, by using a variant of isomorphism allowing to delete degree-2 nodes, called homeomorphism (defined below). For biological motivation, see, e.g., [28]. Homeomorphism: Given a graph G = (V,E) and a subset U of degree-2 nodes in V , generate the multigraph G \ U as follows (see Fig.…”

Section: Problem Statementmentioning

confidence: 99%

Improved Parameterized Algorithms for Network Query Problems

Pinter

Shachnai

Zehavi

2014

Parameterized and Exact Computation

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Abstract. Biological networks are often explored through extensive use of network queries. Partial Information Network Queries (PINQ) address the major challenge of analyzing such networks in the absence of certain topological data. In the PINQ problem, we are given a host graph H, modeling a network, and a pattern P, whose topology is only partially known. We seek a subgraph of H that resembles P. In this paper, we study a generalization of PINQ which allows near resemblance between H and P. We obtain an exact parameterized algorithm as well as an FPT-approximation scheme for a wide class of inputs, where the parameter is the number of nodes in P. Our algorithms substentially improve the best O * running times in solving PINQ, as well as the special cases of the Alignment Network Query problem and the Topology-Free Network Query problem.

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Section: Problem Statementmentioning

confidence: 99%

Improved Parameterized Algorithms for Network Query Problems

Pinter

Shachnai

Zehavi

2014

Parameterized and Exact Computation

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“…This algorithm was used to perform inter-species and intra-species alignments of metabolic pathways [9], and a pathway evolution study [10]. Moreover, it was recently extended to handle a certain family of DAGs [11].…”

Section: Prior Workmentioning

confidence: 99%

Partial Information Network Queries

Pinter

Zehavi

2013

Lecture Notes in Computer Science

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We study the Partial Information Network Query (PINQ) problem, which generalizes two problems that often arise in bioinformatics: the Alignment Network Query (ANQ) problem and the Topology-Free Network Query (TFNQ) problem. In both ANQ and TFNQ we have a pattern P and a graph H, and we seek a subgraph of H that resembles P. ANQ requires knowing the topology of P, while TFNQ ignores it. PINQ fits the scenario where partial information is available on the topology of P. Our main result is a parameterized algorithm that handles inputs for PINQ in which P is a set of trees. This algorithm significantly improves the best known O * running time in solving TFNQ. We also improve the best known O * running times in solving two special cases of ANQ.Keywords: parameterized algorithm, pattern matching, partial information network query, alignment network query, topology-free network query

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“…The main comparative approaches considered so far focus on homogeneous networks using networks alignment (see, among others, [10,11,18,20,5,2,21,12]). Such methods are powerful for detecting conserved modules across several networks of different species.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, pathways in metabolic networks correspond to DAGs [18], while functionally related proteins in PPI networks correspond to connected subgraphs [1,2,15,21,12]). Thus, it is of interest to be able to extract biologically relevant information from two large networks by decomposing them into smaller modules that each (i) carry a rich biological information and (ii) are easier to interpret.…”

Section: Introductionmentioning

confidence: 99%

Algorithmic Aspects of Heterogeneous Biological Networks Comparison

Blin¹,

Fertin

Mohamed-Babou

et al. 2011

Combinatorial Optimization and Applications

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Abstract. Biological networks are commonly used to model molecular activity within the cell. Recent experimental studies have shown that the detection of conserved subnetworks across several networks, coming from different organisms, may allow the discovery of disease pathways and prediction of protein functions. There already exist automatic methods that allow to search for conserved subnetworks using networks alignment; unfortunately, these methods are limited to networks of same type, thus having the same graph representation. Towards overcoming this limitation, a unified framework for pairwise comparison and analysis of networks with different graph representations (in particular, a directed acyclic graph D and an undirected graph G over the same set of vertices) is presented in [4]. We consider here a related problem called k-DAGCC: given a directed graph D and an undirected graph G on the same set V of vertices, and an integer k, does there exist sets of vertices V1, V2, . . .is connected ? Two variants of k-DAGCC are of interest: (a) the Vis must form a partition of V , or (b) the Vis must form a cover of V . We study the computational complexity of both variants of k-DAGCC and, depending on the constraints imposed on the input, provide several polynomial-time algorithms, hardness and inapproximability results.

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Alignment of metabolic pathways

Cited by 182 publications

References 16 publications

Improved Parameterized Algorithms for Network Query Problems

Improved Parameterized Algorithms for Network Query Problems

Partial Information Network Queries

Algorithmic Aspects of Heterogeneous Biological Networks Comparison

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