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Uncovering interactions in the frequency domain

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Guo, Shuixia, Wu, Jianhua, Ding, Mingzhou and Feng, Jianfeng. (2008) Uncovering interactions in the frequency domain. P L o S Computational Biology , Vol.4 (No.5). ISSN 1553-734X

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Official URL: http://dx.doi.org/10.1371/journal.pcbi.1000087

Abstract

Oscillatory activity plays a critical role in regulating biological processes at levels ranging from subcellular, cellular, and network to the whole organism, and often involves a large number of interacting elements. We shed light on this issue by introducing a novel approach called partial Granger causality to reliably reveal interaction patterns in multivariate data with exogenous inputs and latent variables in the frequency domain. The method is extensively tested with toy models, and successfully applied to experimental datasets, including (1) gene microarray data of HeLa cell cycle; (2) in vivo multielectrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of a sheep; and (3) in vivo LFPs recorded from distributed sites in the right hemisphere of a macaque monkey.

Item Type:	Journal Article
Subjects:	Q Science > QH Natural history > QH301 Biology
Divisions:	Faculty of Science > Centre for Scientific Computing Faculty of Science > Computer Science Faculty of Science > Mathematics
Library of Congress Subject Headings (LCSH):	Oscillations, Biological systems, Biology -- Mathematical models, DNA microarrays -- Data processing, Brain -- Data processing
Journal or Publication Title:	P L o S Computational Biology
Publisher:	Public Library of Science
ISSN:	1553-734X
Date:	30 May 2008
Volume:	Vol.4
Number:	No.5
Identification Number:	10.1371/journal.pcbi.1000087
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access
Funder:	Engineering and Physical Sciences Research Council (EPSRC), Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC), European Union (EU)
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URI:	http://wrap.warwick.ac.uk/id/eprint/4438