TY - GEN
T1 - Using directed information for influence discovery in interconnected dynamical systems
AU - Rao, Arvind
AU - Hero, Alfred O.
AU - States, David J.
AU - Engel, James Douglas
N1 - Copyright:
Copyright 2009 Elsevier B.V., All rights reserved.
PY - 2008
Y1 - 2008
N2 - Structure discovery in non-linear dynamical systems is an important and challenging problem that arises in various applications such as computational neuroscience, econometrics, and biological network discovery. Each of these systems have multiple interacting variables and the key problem is the inference of the underlying structure of the systems (which variables are connected to which others) based on the output observations (such as multiple time trajectories of the variables). Since such applications demand the inference of directed relationships among variables in these non-linear systems, current methods that have a linear assumption on structure or yield undirected variable dependencies are insufficient. Hence, in this work, we present a methodology for structure discovery using an informationtheoretic metric called directed time information (DTI). Using both synthetic dynamical systems as well as true biological dataseis (kidney development and T-cell data), we demonstrate the utility of DTI in such problems.
AB - Structure discovery in non-linear dynamical systems is an important and challenging problem that arises in various applications such as computational neuroscience, econometrics, and biological network discovery. Each of these systems have multiple interacting variables and the key problem is the inference of the underlying structure of the systems (which variables are connected to which others) based on the output observations (such as multiple time trajectories of the variables). Since such applications demand the inference of directed relationships among variables in these non-linear systems, current methods that have a linear assumption on structure or yield undirected variable dependencies are insufficient. Hence, in this work, we present a methodology for structure discovery using an informationtheoretic metric called directed time information (DTI). Using both synthetic dynamical systems as well as true biological dataseis (kidney development and T-cell data), we demonstrate the utility of DTI in such problems.
KW - Directed information
KW - Mutual information
KW - Transcription regulatory network
UR - http://www.scopus.com/inward/record.url?scp=57549095201&partnerID=8YFLogxK
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U2 - 10.1117/12.801360
DO - 10.1117/12.801360
M3 - Conference contribution
AN - SCOPUS:57549095201
SN - 9780819472946
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Advanced Signal Processing Algorithms, Architectures, and Implementations XVIII
T2 - Advanced Signal Processing Algorithms, Architectures, and Implementations XVIII
Y2 - 10 August 2008 through 11 August 2008
ER -