Matrisome AnalyzeR – a suite of tools to annotate and quantify ECM molecules in big datasets across organisms is a dataset published in Journal of Cell Science (2023). On theSindex it has a DataRank of 1.1, placing it in the top 18.3% of the data-sharing corpus. It has been cited 60 times, with 53 citing works in its 1-hop citation network.
Ranks in the top 18% for downstream scientific impact
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
0.617
From this paper's citation signal
Citation Network Contribution
0.497
From 27 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 53 citers.
National Institutes of Health
Grant: U01HG012680
National Institutes of Health
Grant: R01CA232517
National Institutes of Health
Grant: R21CA261642
Academy of Finland
Grant: DECISION 326291
Cancer Foundation Finland sr
Grant: 220017
National Institutes of Health
Grant: 1U01HG012680-01
Thinking outside the cell: Leveraging HuBMAP data to build the human ECM atlas
National Institutes of Health
Grant: 5U01HG012680-02
Thinking outside the cell: Leveraging HuBMAP data to build the human ECM atlas
National Institutes of Health
Grant: 1R21CA261642-01A1
Enhanced mass-spectrometry-based approaches for in-depth profiling of the cancer extracellular matrix
National Institutes of Health
Grant: 5R01CA232517-05
Engineered ECM platforms to analyze progression in high grade serous ovarian cancer
University of Illinois Chicago
Cancer Foundation Finland
Finnish Cancer Institute
K. Albin Johansson Foundation
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