Predicting and comparing transcription start sites in single cell populations is a research paper published in PLoS Computational Biology (2025). On theSindex it has a DataRank of 0.165. It has been cited 2 times.
Scored on demand from live citation data
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
0.165
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 Institute of General Medical Sciences
Grant: R35GM142702
NIH HHS
Grant: S10 OD016290
National Institutes of Health
Grant: 1S10OD016290-01A1
Acquisition of a Scalable Storage Cluster for Data Intensive NIH Research
National Institutes of Health
Grant: 1R35GM142702-01
Novel Statistical Methods for Multiscale Analysis of Single-cell Transcriptomes
National Science Foundation
Grant: 1429826
MRI: Acquisition of a Big Data Compute Cluster for Interdisciplinary Research
National Science Foundation
Grant: 2215705
Research Infrastructure: MRI: Acquisition of a Big Data HPC Cluster for Interdisciplinary Research and Training
University of California
FWCI
0.80
Citation Percentile
0.7%
Citation Trend
Fields of Study
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