Erika Dalmo
Forskningsingenjör vid Institutionen för immunologi, genetik och patologi; Forskningsprogram: Neuroonkologi och neurodegeneration; Forskargrupp Bengt Westermark
- E-post:
- erika.dalmo@igp.uu.se
- Besöksadress:
- Dag Hammarskjölds väg 20
751 85 Uppsala - Postadress:
- Rudbecklaboratoriet
751 85 UPPSALA
Publikationer
Senaste publikationer
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p21-Dependent Senescence Induction by BMP4 Renders Glioblastoma Cells Vulnerable to Senolytics
Ingår i International Journal of Molecular Sciences, 2025
- DOI för p21-Dependent Senescence Induction by BMP4 Renders Glioblastoma Cells Vulnerable to Senolytics
- Ladda ner fulltext (pdf) av p21-Dependent Senescence Induction by BMP4 Renders Glioblastoma Cells Vulnerable to Senolytics
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Glioblastoma heterogeneity and plasticity: Investigating the roles of BMP4 and SOX2
2023
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Modeling glioblastoma heterogeneity as a dynamic network of cell states
Ingår i Molecular Systems Biology, 2021
- DOI för Modeling glioblastoma heterogeneity as a dynamic network of cell states
- Ladda ner fulltext (pdf) av Modeling glioblastoma heterogeneity as a dynamic network of cell states
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Modeling glioblastoma heterogeneity as a dynamic network of cell states
Ingår i Molecular Systems Biology, 2021
- DOI för Modeling glioblastoma heterogeneity as a dynamic network of cell states
- Ladda ner fulltext (pdf) av Modeling glioblastoma heterogeneity as a dynamic network of cell states
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Ingår i Molecular Cancer Research, s. 981-991, 2020
Alla publikationer
Artiklar i tidskrift
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p21-Dependent Senescence Induction by BMP4 Renders Glioblastoma Cells Vulnerable to Senolytics
Ingår i International Journal of Molecular Sciences, 2025
- DOI för p21-Dependent Senescence Induction by BMP4 Renders Glioblastoma Cells Vulnerable to Senolytics
- Ladda ner fulltext (pdf) av p21-Dependent Senescence Induction by BMP4 Renders Glioblastoma Cells Vulnerable to Senolytics
-
Modeling glioblastoma heterogeneity as a dynamic network of cell states
Ingår i Molecular Systems Biology, 2021
- DOI för Modeling glioblastoma heterogeneity as a dynamic network of cell states
- Ladda ner fulltext (pdf) av Modeling glioblastoma heterogeneity as a dynamic network of cell states
-
Modeling glioblastoma heterogeneity as a dynamic network of cell states
Ingår i Molecular Systems Biology, 2021
- DOI för Modeling glioblastoma heterogeneity as a dynamic network of cell states
- Ladda ner fulltext (pdf) av Modeling glioblastoma heterogeneity as a dynamic network of cell states
-
Ingår i Molecular Cancer Research, s. 981-991, 2020
-
Sox21 inhibits glioma progression in vivo by reducing Sox2 and stimulating aberrant differentiation
Ingår i International Journal of Cancer, s. 1345-1356, 2013
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Ingår i International Journal of Cancer, s. 1345-1356, 2013
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Ingår i European Journal of Cancer, 2012