Leveraging functional annotation to identify genes associated with complex diseases is a research paper published in PLoS Computational Biology (2020). On theSindex it has a DataRank of 0.999. It has been cited 25 times, with 19 citing works in its 1-hop citation network.
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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
0.489
From this paper's citation signal
Citation Network Contribution
0.511
From 16 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 19 citers.
National Institutes of Health
Grant: R01 GM122078
National Institutes of Health
Grant: P30 AG021342
National Science Foundation
Grant: DMS 1902903
NIGMS NIH HHS
Grant: R01 GM134005
NCATS NIH HHS
Grant: UL1 TR001863
National Institutes of Health
Grant: 1R01GM134005-01A1
Novel statistical methods and tools to integrate multiple endophenotypes and functional annotation data to study the roles of rare variants in complex human diseases using sequencing data
National Science Foundation
Grant: 1902903
New Statistical Methods for High-Dimensional Association Tests with Applications to Large-Scale Genetic Data
National Institutes of Health
Grant: 5R01GM122078-04
Statistical Models for Genetic Studies, Using Network and Integrative Analysis
National Institutes of Health
Grant: 5P30AG021342-13
Information Dissemination Core
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