Discovering Study-Specific Gene Regulatory Networks
- Submitting institution
-
Brunel University London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 009-95922-7041
- Type
- D - Journal article
- DOI
-
10.1371/journal.pone.0106524
- Title of journal
- Plos One
- Article number
- e106524
- First page
- -
- Volume
- 9
- Issue
- 9
- ISSN
- 1932-6203
- Open access status
- Out of scope for open access requirements
- Month of publication
- September
- Year of publication
- 2014
- URL
-
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0106524
- 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
- No
- Number of additional authors
-
5
- Research group(s)
-
1 - Artificial Intelligence (AI)
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper developed a novel method for identifying "unique networks" as opposed to "consensus networks" whereby gene pathways only appeared for specific conditions. Early work was published in the Intelligent Data Analysis conference series (A-ranked conference by CORE). It was initially developed for wheat but has also been used to explore cancer-specific pathways resulting in the identification of a new biomarker for Lung and Ovarian Cancers. This was published in Carcinogenesis (https://doi.org/10.1093/carcin/bgx122). It also went on to form the basis for the technology used in Food and Energy Security (https://doi.org/10.1002/fes3.126).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
