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Comparison of large networks with sub-sampling strategies

Abstract:

Networks are routinely used to represent large data sets, making the comparison of networks a tantalizing research question in many areas. Techniques for such analysis vary from simply comparing network summary statistics to sophisticated but computationally expensive alignment-based approaches. Most existing methods either do not generalize well to different types of networks or do not provide a quantitative similarity score between networks. In contrast, alignment-free topology based networ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/srep28955

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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Societies, Other & Subsidiary Companies
Department:
Kellogg College
Oxford college:
Kellogg College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
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Grant:
Oxford Center for Integrated Systems Biology (OCISB
Systems Biology Doctoral Training Center (DTC)
Publisher:
Nature Publishing Group Publisher's website
Journal:
Scientific Reports Journal website
Publication date:
2016-07-06
Acceptance date:
2016-06-07
DOI:
EISSN:
2045-2322
ISSN:
2045-2322
Source identifiers:
627921
Language:
English
Keywords:
Pubs id:
pubs:627921
UUID:
uuid:2d8992f0-165a-4237-9d5b-6b46bfa78d2e
Local pid:
pubs:627921
Deposit date:
2016-08-11

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