- author = "Fergal Reid and Neil Hurley",
- title = "Analysing structure in complex networks using quality functions evolved by genetic programming",
- booktitle = "GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation",
- year = "2011",
- editor = "Natalio Krasnogor and Pier Luca Lanzi and Andries Engelbrecht and David Pelta and Carlos Gershenson and Giovanni Squillero and Alex Freitas and Marylyn Ritchie and Mike Preuss and Christian Gagne and Yew Soon Ong and Guenther Raidl and Marcus Gallager and Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and Nikolaus Hansen and Silja Meyer-Nieberg and Jim Smith and Gus Eiben and Ester Bernado-Mansilla and Will Browne and Lee Spector and Tina Yu and Jeff Clune and Greg Hornby and Man-Leung Wong and Pierre Collet and Steve Gustafson and Jean-Paul Watson and Moshe Sipper and Simon Poulding and Gabriela Ochoa and Marc Schoenauer and Carsten Witt and Anne Auger",
- isbn13 = "978-1-4503-0557-0",
- pages = "283--290",
- keywords = "genetic algorithms, genetic programming, Bioinformatics, computational, systems, and synthetic biology",
- month = "12-16 " # jul,
- organisation = "SIGEVO",
- address = "Dublin, Ireland",
-
DOI = "
doi:10.1145/2001576.2001616",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
-
abstract = "When studying complex networks, we are often
interested in identifying structures within the
networks. Previous work has successfully used
algorithmically identified network structures to
predict functional groups; for example, where
structures extracted from protein-protein interaction
networks have been predictive of functional protein
complexes. One way structures in complex networks have
previously been described is as collections of nodes
that maximise a local quality function.
For a particular set of structures, we search the space of quality functions using Genetic Programming, to find a function that locally describes that set of structures. This technique allows us to investigate the common network properties of defined sets of structures. We also use this technique to classify and differentiate between different types of structure. We apply this method on several synthetic benchmarks, and on a protein-protein interaction network. Our results indicate this is a useful technique of investigating properties that sets of network structures have in common.",
- notes = "Also known as \cite{2001616} GECCO-2011 A joint meeting of the twentieth international conference on genetic algorithms (ICGA-2011) and the sixteenth annual genetic programming conference (GP-2011)",
