Title
Extracting directed information flow networks: an application to genetics and semantics
Abstract
We introduce a general method to infer the directional information flow between populations whose elements are described by n-dimensional vectors of symbolic attributes. The method is based on the Jensen-Shannon divergence and on the Shannon entropy and has a wide range of application. We show here the results of two applications: first we extract the network of genetic flow between meadows of the seagrass Poseidonia oceanica, where the meadow elements are specified by sets of microsatellite markers, and then we extract the semantic flow network from a set of Wikipedia pages, showing the semantic channels between different areas of knowledge.
Year
DOI
Venue
2010
10.1103/PhysRevE.83.026103
PHYSICAL REVIEW E
Keywords
Field
DocType
jensen shannon divergence,genetics,shannon entropy,information flow
Information flow (information theory),Divergence,Communication channel,Theoretical computer science,Statistics,Entropy (information theory),Classical mechanics,Semantics,Physics
Journal
Volume
Issue
ISSN
83
2
1539-3755
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
A. P. Masucci1322.63
Víctor M. Eguíluz211314.14
E. Hernandez-Garcia3293.58
A. Kalampokis4212.31