An individualized causal framework for learning intercellular communication networks that define microenvironments of individual tumors is a research paper published in PLoS Computational Biology (2022). On theSindex it has a DataRank of 0.360. It has been cited 10 times.
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Base Score Contribution
0.360
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.
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Grant: R01LM012011
National Cancer Institute
Grant: R01CA254274
National Human Genome Research Institute
Grant: U54HG008540
National Institutes of Health
Grant: 3U54HG008540-02S1
Center for causal Modeling and discovery of Biomedical Knowledge from Big Data
National Institutes of Health
Grant: 5R01LM012011-10
Interpretable deep learning models for translational medicine Renewal
National Institutes of Health
Grant: 5R01CA254274-06
Study of the IL-33-driven immune cell organization underpinning responses to immune checkpoint blockade cancer therapy
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Sustainable Development Goals