Reference : Relations between the set-complexity and the structure of graphs and their sub-graphs
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/13386
Relations between the set-complexity and the structure of graphs and their sub-graphs
English
Ignac, Tomasz mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Sakhanenko, Nikita mailto [> >]
Galas, David J. [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
2012
EURASIP Journal on Bioinformatics & Systems Biology
13
Yes (verified by ORBilu)
International
1687-4145
[en] Set-complexity ; Biological networks ; Modularity ; Modular graphs ; Bipartite graphs ; Multi-partite graphs
[en] We describe some new conceptual tools for the rigorous, mathematical description of the “set-complexity” of graphs. This set-complexity has been shown previously to be a useful measure for analyzing some biological networks, and in discussing biological information in a quantitative fashion. The advances described here allow us to define some significant relationships between the set-complexity measure and the structure of graphs, and of their component sub-graphs. We show here that modular graph structures tend to maximize the set-complexity of graphs. We point out the relationship between modularity and redundancy, and discuss the significance of set-complexity in this regard. We specifically discuss the relationship between complexity and entropy in the case of complete-bipartite graphs, and present a new method for constructing highly complex, binary graphs. These results can be extended to the case of ternary graphs, and to other multi-edge graphs, which are fundamentally more relevant to biological structures and systems. Finally, our results lead us to an approach for extracting high complexity modular graphs from large, noisy graphs with low information content. We illustrate this approach with two examples.
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) ; Luxembourg Centre for Systems Biomedicine (LCSB): Experimental Neurobiology (Balling Group)
http://hdl.handle.net/10993/13386
also: http://hdl.handle.net/10993/26580
10.1186/1687-4153-2012-13

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
Ignac, Sakhanenko, Galas 2012.pdfPublisher postprint827.14 kBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.