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Directed Shortest Walk on Temporal Graphs

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AbstractBackgroundThe use of graphs as a way of abstracting and representing biological systems has provided a powerful analysis paradigm. Specifically, graph optimization algorithms are routinely used to address various connectivity queries, such as finding paths between proteins in a protein-protein interaction network, while maximizing objectives such as parsimony. While present studies in this field mostly concern static graphs, new types of data now motivate the need to account for changes that might occur to the elements (nodes) that are represented by the graph on the relationships (edges) between them.Results and DiscussionWe define the notion of Directed Temporal Graphs as a series of directed subgraphs of an underlying graph, ordered by time, where only a subset of vertices and edges are present. We then build up towards the Time Conditioned Shortest Walk problem on Directed Temporal Graphs: given a series of time ordered directed graphs, find the shortest walk from any given source node at time point 1 to a target node at time T ≥ 1, such that the walk is consistent (monotonically increasing) with the timing of nodes and edges. We show, contrary to the Directed Shortest Walk problem which can be solved in polynomial time, that the Time Conditioned Shortest Walk (TCSW) problem is NP-Hard, and is hard to approximate to factor for T ≥ 3 and ε > 0. Lastly, we develop an integer linear program to solve a generalized version of TCSW, and demonstrate its ability to reach optimality with instances of the human protein interaction network.ConclusionWe demonstrate that when extending the shortest walk problem in computational biology to account for multiple ordered conditions, the problem not only becomes hard to solve, but hard to approximate, a limitation which we address via a new solver. From this narrow definition of TCSW, we relax the constraint of time consistency within the shortest walk, deriving a direct relationship between hardness of approximation and the allowable step size in our walk between time conditioned networks. Lastly we briefly explore a variety of alternative formulations for this problem, providing insight into both tractable and intractable variants.AvailabilityOur solver for the general k-Time Condition Shortest Walk problem is available at https://github.com/YosefLab/temporal_condition_shortest_walk
Cold Spring Harbor Laboratory
Title: Directed Shortest Walk on Temporal Graphs
Description:
AbstractBackgroundThe use of graphs as a way of abstracting and representing biological systems has provided a powerful analysis paradigm.
Specifically, graph optimization algorithms are routinely used to address various connectivity queries, such as finding paths between proteins in a protein-protein interaction network, while maximizing objectives such as parsimony.
While present studies in this field mostly concern static graphs, new types of data now motivate the need to account for changes that might occur to the elements (nodes) that are represented by the graph on the relationships (edges) between them.
Results and DiscussionWe define the notion of Directed Temporal Graphs as a series of directed subgraphs of an underlying graph, ordered by time, where only a subset of vertices and edges are present.
We then build up towards the Time Conditioned Shortest Walk problem on Directed Temporal Graphs: given a series of time ordered directed graphs, find the shortest walk from any given source node at time point 1 to a target node at time T ≥ 1, such that the walk is consistent (monotonically increasing) with the timing of nodes and edges.
We show, contrary to the Directed Shortest Walk problem which can be solved in polynomial time, that the Time Conditioned Shortest Walk (TCSW) problem is NP-Hard, and is hard to approximate to factor for T ≥ 3 and ε > 0.
Lastly, we develop an integer linear program to solve a generalized version of TCSW, and demonstrate its ability to reach optimality with instances of the human protein interaction network.
ConclusionWe demonstrate that when extending the shortest walk problem in computational biology to account for multiple ordered conditions, the problem not only becomes hard to solve, but hard to approximate, a limitation which we address via a new solver.
From this narrow definition of TCSW, we relax the constraint of time consistency within the shortest walk, deriving a direct relationship between hardness of approximation and the allowable step size in our walk between time conditioned networks.
Lastly we briefly explore a variety of alternative formulations for this problem, providing insight into both tractable and intractable variants.
AvailabilityOur solver for the general k-Time Condition Shortest Walk problem is available at https://github.
com/YosefLab/temporal_condition_shortest_walk.

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