Natural selection of immune and metabolic genes associated with health in two lowland Bolivian populations is a research paper published in Proceedings of the National Academy of Sciences (2022). On theSindex it has a DataRank of 0.510. It has been cited 29 times.
Scored on demand from live citation data
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DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
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Base Score Contribution
0.510
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →NHLBI NIH HHS
Grant: R01 HL147853
NHLBI NIH HHS
Grant: T32 HL007055
NIA NIH HHS
Grant: R01 AG054442
NHLBI NIH HHS
Grant: T32 HL129982
NIA NIH HHS
Grant: RF1 AG054442
NIA NIH HHS
Grant: R56 AG024119
NIA NIH HHS
Grant: R01 AG024119
French National Research Agency (ANR)
Grant: ANR-17-EURE-0010
National Institutes of Health
Grant: 3RF1AG054442-02S2
Brain atrophy, cognitive impairment, and Alzheimer's in a low CVD-risk population
National Institutes of Health
Grant: 3R01AG024119-07S2
The Human Life Course and the Biodemography of Aging
FWCI
4.45
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of Population genetic admixture and evolutionary history in the Shandong Peninsula inferred from integrative modern and ancient genomic resources
Additional file 1 of Population genetic admixture and evolutionary history in the Shandong Peninsula inferred from integrative modern and ancient genomic resources
Additional file 2 of Population genetic admixture and evolutionary history in the Shandong Peninsula inferred from integrative modern and ancient genomic resources
Additional file 2 of Population genetic admixture and evolutionary history in the Shandong Peninsula inferred from integrative modern and ancient genomic resources