Systematic analysis of the gerontome reveals links between aging and age-related diseases
- Submitting institution
-
Birkbeck College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 200
- Type
- D - Journal article
- DOI
-
10.1093/hmg/ddw307
- Title of journal
- Human Molecular Genetics
- Article number
- -
- First page
- 4804
- Volume
- 25
- Issue
- 21
- ISSN
- 0964-6906
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2016
- URL
-
http://eprints.bbk.ac.uk/id/eprint/30711/
- 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
-
10
- Research group(s)
-
2 - Experimental Data Science
- Citation count
- 33
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This article conducts the largest system-level analysis of the genetics of ageing across species by using state-of-the-art machine learning and bioinformatics methods. This analysis successfully revealed novel ageing-related pathways and genes, and discovered the relationships between ageing-related genes and ageing-related diseases, including the roles of those ageing-related diseases genes in the human gene interactome. Further analysis of those genes by the authors successfully predicted novel life-extending drugs (reported in the paper's Supplementary Materials).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -