Vitamin E Enhances Cancer Immunotherapy by Reinvigorating Dendritic Cells via Targeting Checkpoint SHP1 is a research paper published in Cancer Discovery (2022). On theSindex it has a DataRank of 3.2. It has been cited 133 times, with 109 citing works in its 1-hop citation network.
Scored on demand from live citation data
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DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
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Base Score Contribution
0.735
From this paper's citation signal
Citation Network Contribution
2.5
From 91 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 109 citers.
NIH
Grant: R01CA184836
NIH
Grant: R01CA208213
NIH
Grant: R01CA231149
METAVivor research
Grant: 56675
METAVivor research
Grant: 58284
MD Anderson Duncan Family Institute for Cancer Prevention and Risk Assessment NIH Cancer Center Support Grant
Grant: P30CA016672
Cancer Prevention Research Institute of Texas
Grant: RP180813
NIH
Grant: P01CA092584
NIH
Grant: R35CA220430
National Institutes of Health
Grant: 5R01CA208213-04
Inhibition of brain metastasis by blocking MAPK12 driver kinase functions
National Institutes of Health
Grant: 5R35CA220430-02
Mesocale And Nanoscale Technologies Integrated by Structures for DNA Repair Complexes (MANTIS-DRC)
National Institutes of Health
Grant: 5R01CA184836-02
Target p70S6K for Chemodietary Prevention/Early Intervention of ER- Breast Cancer
National Institutes of Health
Grant: 3P30CA016672-41S4
Cancer Center Support (CORE) Grant
National Institutes of Health
Grant: 3P01CA092584-19S1
Structural Cell Biology of DNA Repair Machines
National Institutes of Health
Grant: 5R01CA231149-02
Combating Breast Cancer Brain Metastasis by Blocking the Two-Pronged Driver Kinase Function of CDK5
FWCI
11.17
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 1 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 2 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 2 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 3 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 3 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 4 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 4 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 5 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 5 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 6 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 6 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 7 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 7 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 8 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 8 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 9 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 9 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 10 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas
Additional file 10 of Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas