Network Elucidation Template: A framework for human-guided network inference

Authors:
Leo Lopes;Jay Konieczka;Victor Foulk;Parker Antin
Affiliations:
Systems and Industrial Engineering, University of Arizona, Tucson, AZ 85721, United States;O'Shea Lab, Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, United States;Naval Reactors, United States Navy, Washington, DC 20004, United States;Cellular Biology and Anatomy, University of Arizona, Tucson, AZ 85721, United States
Venue:
Computers and Industrial Engineering
Year:
2010

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Abstract

Network elucidation is the problem of inferring all parameters of a network from a subset of those parameters. We introduce the Network Elucidation Template (NET), which provides a framework upon which algorithms for such problems can be built. NET algorithms take advantage of novel methods for collaboration between human operators and computers. They use visualizations of the peculiar structures that appear in optimal solutions to aid the parameter search. By design, NET is at a high enough level of abstraction to describe a class of algorithms, as opposed to a single algorithm. Given a problem, and the structure of that problem, an effective instantiation of the template into an algorithm can be created. We describe one such instantiation: using a network flow framework to implement a NET algorithm for uncovering smuggling networks; as well as the general template.