Incorporating heuristics in a swarm intelligence framework for inferring gene regulatory networks from gene expression time series

Kyriakos Kentzoglanakis, Matthew Poole, Carl Adams

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

88 Downloads (Pure)

Abstract

In this paper, we address the problem of reverse-engineering a gene regulatory network from gene expression time series. We approach the problem by implementing an ant system to generate candidate network structures. The quality of a candidate structure is evaluated using a particle swarm optimization algorithm that tunes the parameters of the corresponding model, by minimizing the error between the actual time series and the trained model’s output. We extend this approach by incorporating domain-specific heuristics to the ant system, as a mechanism that has the potential to bias the pheromone amplification effect towards biologically plausible relationships. We apply the method to a subset of genes from a real world data set and report on the results.
Original languageEnglish
Title of host publicationAnt colony optimization and swarm intelligence: 6th International Conference, ANTS 2008, Brussels, Belgium, September 22-24, 2008, Proceedings
EditorsM Dorigo, M Birattari, C Blum, M Clerc, T Stützle, A Winfield
Place of PublicationBerlin
PublisherSpringer
Pages323-330
Number of pages8
Edition5217
ISBN (Print)978-3540875260
Publication statusPublished - 2008

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Number5217

Fingerprint

Dive into the research topics of 'Incorporating heuristics in a swarm intelligence framework for inferring gene regulatory networks from gene expression time series'. Together they form a unique fingerprint.

Cite this