Exploring neighborhoods in large metagenome assembly graphs reveals hidden sequence diversity
- Submitting institution
-
Birkbeck College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 766
- Type
- D - Journal article
- DOI
-
10.1186/s13059-020-02066-4
- Title of journal
- Genome Biology
- Article number
- -
- First page
- 1
- Volume
- 21
- Issue
- 164
- ISSN
- 1474-760X
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2020
- URL
-
http://eprints.bbk.ac.uk/id/eprint/32137/
- 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
-
5
- Research group(s)
-
1 - Algorithms, Verification and Software
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Our work applies recent insights from structural and algorithmic graph theory to extract biologically useful regions from metagenome graphs. Our implementation (https://github.com/spacegraphcats/spacegraphcats) is actively used by bioinformatics researchers as witnessed by the frequent feedback and questions we receive via github. One of the UC Davis collaborators has recently received a NIH grant to continue her work with the software while a large NIH grant aimed at extending the software that spans three institutions (Birkbeck, UC Davis, University of Utah) is currently under review.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -