Abstract
BackgroundThe alignment of protein-protein interaction networks was recently formulated as an integer quadratic programming problem, along with a linearization that can be solved by integer linear programming software tools. However, the resulting integer linear program has a huge number of variables and constraints, rendering it of no practical use.ResultsWe present a compact integer linear programming reformulation of the protein-protein interaction network alignment problem, which can be solved using state-of-the-art mathematical modeling and integer linear programming software tools, along with empirical results showing that small biological networks, such as virus-host protein-protein interaction networks, can be aligned in a reasonable amount of time on a personal computer and the resulting alignments are structurally coherent and biologically meaningful.ConclusionsThe implementation of the integer linear programming reformulation using current mathematical modeling and integer linear programming software tools provided biologically meaningful alignments of virus-host protein-protein interaction networks.
Highlights
The alignment of protein-protein interaction networks was recently formulated as an integer quadratic programming problem, along with a linearization that can be solved by integer linear programming software tools
An exact solution to the network alignment problem can be obtained by an integer quadratic programming formulation [6], but its linearization [7] has a huge number of binary variables and constraints
We present a compact integer linear programming reformulation of the protein-protein interaction network alignment problem, which can be solved using state-of-the-art mathematical modeling and integer linear programming software tools
Summary
The alignment of protein-protein interaction networks was recently formulated as an integer quadratic programming problem, along with a linearization that can be solved by integer linear programming software tools. Several methods and software tools have been already introduced for the alignment of biological networks, including protein-protein interaction networks, metabolic pathways, and gene regulatory networks. They are addressed to solve interesting biological questions, such as the inference of protein-protein interactions and protein functions, the regulation of biological processes, and the metabolic capabilities of microorganisms. An exact solution to the network alignment problem can be obtained by an integer quadratic programming formulation [6], but its linearization [7] has a huge number of binary variables and constraints
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