Abstract
We undertake an extensive numerical investigation of the graph spectra of thousands regular graphs, a set of random Erdös-Rényi graphs, the two most popular types of complex networks and an evolving genetic network by using novel conceptual and experimental tools. Our objective in so doing is to contribute to an understanding of the meaning of the Eigenvalues of a graph relative to its topological and informationtheoretic properties. We introduce a technique for identifying the most informative Eigenvalues of evolving networks by comparing graph spectra behavior to their algorithmic complexity. We suggest that extending techniques can be used to further investigate the behavior of evolving biological networks. In the extended version of this paper we apply these techniques to seven tissue specific regulatory networks as static example and network of a naïve pluripotent immune cell in the process of differentiating towards a Th17 cell as evolving example, finding the most and least informative Eigenvalues at every stage.
Original language | English (US) |
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Title of host publication | Bioinformatics and Biomedical Engineering - 3rd International Conference, IWBBIO 2015, Proceedings |
Editors | Francisco Ortuño, Ignacio Rojas |
Publisher | Springer Verlag |
Pages | 395-405 |
Number of pages | 11 |
ISBN (Electronic) | 9783319164793 |
DOIs | |
State | Published - 2015 |
Externally published | Yes |
Event | 3rd International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2015 - Granada, Spain Duration: Apr 15 2015 → Apr 17 2015 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 9044 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Other
Other | 3rd International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2015 |
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Country/Territory | Spain |
City | Granada |
Period | 04/15/15 → 04/17/15 |
Bibliographical note
Publisher Copyright:© Springer International Publishing Switzerland 2015.
Keywords
- Algorithmic complexity
- Algorithmic probability
- Eigenvalues meaning
- Graph spectra behavior
- Information content
- Network science
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science