Reconstructing phylogenetic level-1 networks from nondense binet and trinet sets
- Submitting institution
-
The University of East Anglia
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 182619967
- Type
- D - Journal article
- DOI
-
10.1007/s00453-015-0069-8
- Title of journal
- Algorithmica
- Article number
- -
- First page
- 173
- Volume
- 77
- Issue
- 1
- ISSN
- 0178-4617
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2017
- 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
-
4
- Research group(s)
-
-
- Citation count
- 13
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- We develop one of the first supernetwork methods for reconstructing phylogenetic networks, which provides a novel tool for researchers to study complex non-tree-like evolutionary processes such as crop hybridization and virus recombination. Our work has motivated two Ph.D. theses (James Oldman at UEA and Jiafan Zhu at Rice University) and several new algorithms for building phylogenetic networks (Journal of Computational Biology, 25: 740-754, 2018; Bioinformatics, 35: i370–i378, 2019; Journal of Theoretical Biology, 489: 110144, 2020), including one that is implemented in the open source software TriLoNet (https://www.uea.ac.uk/groups-and-centres/computational-biology/software/trilonet).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -