Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis is a research paper published in Nature Genetics (2024). On theSindex it has a DataRank of 0.639. It has been cited 70 times.
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Base Score Contribution
0.639
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 →U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute
Grant: U01 HG012103
U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute
Grant: R00HG012203
U.S. Department of Health & Human Services | NIH | National Cancer Institute
Grant: U54 CA274492
U.S. Department of Health & Human Services | NIH | National Cancer Institute
Grant: P30CA008748
U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences
Grant: R35-GM141795
National Institutes of Health
Grant: 5U01HG012103-03
Deciphering the Genomics of Gene Network Regulation of T Cell and Fibroblast States in Autoimmune Inflammation
National Institutes of Health
Grant: 5R00HG012203-05
New approaches for leveraging single-cell data to identify disease-critical genes and gene sets
National Institutes of Health
Grant: 5R35GM141795-04
Methods to Elucidate the Dynamics of Transcriptional Regulation and Chromatin
National Institutes of Health
Grant: 1U54CA274492-01
The Center for Tumor-Immune Systems Biology at MSKCC
National Institutes of Health
Grant: 2P30CA008748-43
MOUSE GENETICS
NHGRI NIH HHS
Grant: U01 HG007893
NIGMS NIH HHS
Grant: T32 GM132083
NIGMS NIH HHS
Grant: R35 GM141795
FWCI
11.12
Citation Percentile
1.0%
Citation Trend
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