A computational framework for the prioritization of disease-gene candidates
- Submitting institution
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University of Ulster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 76407192
- Type
- D - Journal article
- DOI
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10.1186/1471-2164-16-S9-S2
- Title of journal
- BMC Genomics
- Article number
- S2 (2015)
- First page
- -
- Volume
- 16
- Issue
- -
- ISSN
- 1471-2164
- Open access status
- Out of scope for open access requirements
- Month of publication
- August
- Year of publication
- 2015
- URL
-
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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B - Artificial Intelligence Research Centre
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- <28> Network research in this paper has led to a grant application and subsequent funded project MetaPlat (EU Horizon2020 MSCA-RISE grant no. 690998, 12/2015–12/2019). The integrative network approach led to further research disseminated in (10.1007/s13042-016-0503-5, 10.1109/TCBB.2018.2858808, 10.1109/BIBM.2018.8621104, 10.1109/BIBM.2018.8621543). The proposed framework applying “omic” data integration was extended to the area of metagenomics where a University-funded PhD project (Dr Jyotsna Wassan, 2016-2019) focused on the impact of data integration applied to metagenomic data. Research impact in terms of application in an industrial setting has been achieved through the successful Innovate UK funded KTP project (Datactics, KTP11199, 2018-2020).
- Author contribution statement
- -
- Non-English
- No
- English abstract
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