Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning is a research paper published in Computational and Structural Biotechnology Journal (2022). On theSindex it has a DataRank of 0.598. It has been cited 53 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
0.598
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 →Arizona Department of Health Services
Grant: 211002
Arizona Biomedical Research Commission
Grant: 0011
Arizona Biomedical Research Commission
Grant: 05-901
Arizona Biomedical Research Commission
Grant: 1001
Arizona Biomedical Research Commission
Grant: 4001
A. Alfred Taubman Medical Research Institute
Grant: P30AG066462
A. Alfred Taubman Medical Research Institute
Grant: P50AG008702
National Institute of General Medical Sciences
Grant: K01-AG056673
National Institute of General Medical Sciences
Grant: R01-GM131399
National Institute of General Medical Sciences
Grant: R35-GM126985
National Institute of General Medical Sciences
Grant: R56-AG066782-01
National Institute of General Medical Sciences
Grant: U54-AG075931
National Science Foundation
Grant: AARF-17-505009
National Institutes of Health
Grant: NSF1945971
National Institutes of Health
Grant: P30-AG19610
National Institutes of Health
Grant: U24-NS072026
FWCI
3.60
Citation Percentile
0.9%
Influential Citations
2
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals