Systematic discovery of complex insertions and deletions in human cancers is a research paper published in Nature Medicine (2015). On theSindex it has a DataRank of 4.4. It has been cited 131 times, with 89 citing works in its 1-hop citation network.
Scored on demand from live citation data
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.732
From this paper's citation signal
Citation Network Contribution
3.7
From 77 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 89 citers.
NHGRI NIH HHS
Grant: U01 HG006517
NIGMS NIH HHS
Grant: GM 007067
NIGMS NIH HHS
Grant: T32 GM007067
NCI NIH HHS
Grant: R01 CA180006
NIDDK NIH HHS
Grant: R01DK087960
NHGRI NIH HHS
Grant: T32 HG000045
FWCI
4.01
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 1 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 4 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 4 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 5 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 5 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 6 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 6 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 7 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 7 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 8 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 8 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 9 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 9 of Comparison of sequencing data processing pipelines and application to underrepresented African human populations
Additional file 1 of A promising Prognostic risk model for advanced renal cell carcinoma (RCC) with immune-related genes
Additional file 1 of A promising Prognostic risk model for advanced renal cell carcinoma (RCC) with immune-related genes
Additional file 2 of A promising Prognostic risk model for advanced renal cell carcinoma (RCC) with immune-related genes
Additional file 2 of A promising Prognostic risk model for advanced renal cell carcinoma (RCC) with immune-related genes
Additional file 3 of A promising Prognostic risk model for advanced renal cell carcinoma (RCC) with immune-related genes
Additional file 3 of A promising Prognostic risk model for advanced renal cell carcinoma (RCC) with immune-related genes