Heat Shock Proteins and HSF1 in Cancer is a research paper published in Frontiers in Oncology (2022). On theSindex it has a DataRank of 0. It has been cited 111 times.
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National Institutes of Health
Grant: ES031979, ES031002, ES028072
NIEHS NIH HHS
Grant: R01 ES028072
NIEHS NIH HHS
Grant: R01 ES031979
NIEHS NIH HHS
Grant: R01 ES031002
National Institutes of Health
Grant: 1R01ES031002-01A1
Indirect Genotoxicity in Metal Carcinogenesis
National Institutes of Health
Grant: 5R01ES031979-05
Nickel and toxic topoisomerase I products
National Institutes of Health
Grant: 1R01ES028072-01A1
Regulation of p53 and Checkpoint Signaling by Chromium(VI)
FWCI
7.84
Citation Percentile
1.0%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals
Additional file 6 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis
Additional file 6 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis
Additional file 2 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis
Additional file 3 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis
Additional file 3 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis
Additional file 5 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis
Additional file 4 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis
Additional file 4 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis
Additional file 5 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis
Additional file 1 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis
Additional file 1 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis
Additional file 2 of Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis