Uncertainty quantification in variable selection for genetic fine-mapping using bayesian neural networks is a research paper published in iScience (2022). On theSindex it has a DataRank of 0.208. It has been cited 3 times.
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Base Score Contribution
0.208
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 →National Institutes of Health
Grant: R01 GM118652
National Institutes of Health
Grant: R35 GM139628
Wellcome Trust
Grant: 076113
The genetics of weight, BMI, adiposity and obesity
Wellcome Trust
Grant: 085475
WTCCC2 core activities
Wellcome Trust
Grant: 090355
WTCCC3 core activities.
National Science Foundation
Grant: DBI1452622
Medical Research Council
Grant: MC_QA137853
Medical Research Council
Grant: MC_PC_17228
National Institutes of Health
Grant: 1R01GM118652-01
Novel statistical methods to localize genomic elements underlying adaptive evolution
National Institutes of Health
Grant: 1R35GM139628-01
Novel population-genetic methods for localizing targets of natural selection in diverse human genomes
National Science Foundation
Grant: 1452622
CAREER: Next-generation inference of evolutionary paramaters from genome-wide sequence data
David and Lucile Packard Foundation
Wellcome Trust
Wellcome Trust
FWCI
0.51
Citation Percentile
0.7%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals