Deciphering tumor ecosystems at super resolution from spatial transcriptomics with TESLA is a research paper published in Cell Systems (2023). On theSindex it has a DataRank of 0. It has been cited 96 times.
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.
Andrew Sabin Family Foundation
Grant: RP200385
National Institutes of Health
Grant: P01AG066597
Cancer Prevention and Research Institute of Texas
Grant: RP220101
NCI NIH HHS
Grant: R01 CA272863
National Institutes of Health
Grant: R01GM125301
National Institutes of Health
Grant: U01CA264583
National Institutes of Health
Grant: 5P01AG066597-02
From cells to complex syndromes: using networks to understand heterogeneity in TDP-related frontotemporal degeneration and aging
National Institutes of Health
Grant: 5R01GM125301-02
Statistical Methods for Single-Cell Transcriptomics
National Institutes of Health
Grant: 5U01CA264583-03
Spatial and temporal tumor-immune co-evolution and interactions that model lung adenocarcinoma development
University of Texas MD Anderson Cancer Center
Biogen
FWCI
9.32
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals