FlatNJ: A novel network-based approach to visualize evolutionary and biogeographical relationships
- Submitting institution
-
The University of East Anglia
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 182619041
- Type
- D - Journal article
- DOI
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10.1093/sysbio/syu001
- Title of journal
- Systematic Biology
- Article number
- -
- First page
- 383
- Volume
- 63
- Issue
- 3
- ISSN
- 1063-5157
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Phylogenetic networks are used to analyse the evolution of organisms that evolve by crossing with one another to form new species (e.g. new crop plants or dangerous viruses). We develop a new algorithm to generate phylogenetic networks based on a novel combinatorial approach to visualise data in the plane called flat split systems. The algorithm was implemented with collaborators in the BBSRC-funded Earlham Institute in the SPECTRE program (Bioinformatics 34, 2018, 1056-1057, www/earlham.ac.uk/spectre). It has also led to new directions in the theory of oriented matroids (SIAM Journal on Discrete Mathematics, 2017, 31, 839-856).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -