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CC BY V4.0, Open Access
Journal article
A nearest-neighbors network model for sequence data reveals new insight into genotype distribution of a pathogen
BMC bioinformatics, Vol.19(1), pp.475-475
12/12/2018
Handle:
https://hdl.handle.net/2376/113043
PMCID: PMC6291930
PMID: 30541438
Abstract
We demonstrate that using approximate distance measures to rapidly construct similarity networks may lead to significant deficiencies in the structure of that network in terms centrality and clustering analyses. We present a new network representation that maintains the structural semantics of threshold-based networks while increasing connectedness, and an algorithm for constructing the network using exact distance measures in a fraction of the time it would take to build a threshold-based equivalent.
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Details
- Title
- A nearest-neighbors network model for sequence data reveals new insight into genotype distribution of a pathogen
- Creators
- Helen N Catanese - Pullman, WA USAKelly A Brayton - Pullman, WA USAAssefaw H Gebremedhin - Pullman, WA USA
- Publication Details
- BMC bioinformatics, Vol.19(1), pp.475-475
- Academic Unit
- School of Electrical Engineering and Computer Science; Department of Veterinary Microbiology and Pathology
- Publisher
- BioMed Central; London
- Grant note
- IIS-1553528 / ;
- Identifiers
- 99900548008901842
- Language
- English
- Resource Type
- Journal article