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Reverse Engineering of Dynamic Networks
Author(s) -
STIGLER B.,
JARRAH A.,
STILLMAN M.,
LAUBENBACHER R.
Publication year - 2007
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1196/annals.1407.012
Subject(s) - computer science , reverse engineering , set (abstract data type) , dynamic network analysis , dynamic data , gene regulatory network , diagram , biology , computer network , gene , biochemistry , gene expression , database , programming language
: We consider the problem of reverse‐engineering dynamic models of biochemical networks from experimental data using polynomial dynamic systems. In earlier work, we developed an algorithm to identify minimal wiring diagrams , that is, directed graphs that represent the causal relationships between network variables. Here we extend this algorithm to identify a most likely dynamic model from the set of all possible dynamic models that fit the data over a fixed wiring diagram. To illustrate its performance, the method is applied to simulated time‐course data from a published gene regulatory network in the fruitfly Drosophila melanogaster .