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Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas
Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas
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Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas

van IJzendoorn, David G P ; Szuhai, Karoly ; Briaire-de Bruijn, Inge H ; Kostine, Marie ; Kuijjer, Marieke L ; Bovée, Judith V M G Ioshikhes, Ilya

PLoS computational biology, 2019-02, Vol.15 (2), p.e1006826-e1006826 [Periódico revisado por pares]

United States: Public Library of Science

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2
Gene expression profiles of CMS2-epithelial/canonical colorectal cancers are largely driven by DNA copy number gains
Gene expression profiles of CMS2-epithelial/canonical colorectal cancers are largely driven by DNA copy number gains
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Gene expression profiles of CMS2-epithelial/canonical colorectal cancers are largely driven by DNA copy number gains

Berg, Kaja C G ; Sveen, Anita ; Høland, Maren ; Alagaratnam, Sharmini ; Berg, Marianne ; Danielsen, Stine A ; Nesbakken, Arild ; Søreide, Kjetil ; Lothe, Ragnhild A

Oncogene, 2019-08, Vol.38 (33), p.6109-6122 [Periódico revisado por pares]

England: Nature Publishing Group

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3
Tissue and imaging biomarkers for hypoxia predict poor outcome in endometrial cancer
Tissue and imaging biomarkers for hypoxia predict poor outcome in endometrial cancer
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Tissue and imaging biomarkers for hypoxia predict poor outcome in endometrial cancer

Berg, Anna ; Fasmer, Kristine E ; Mauland, Karen K ; Ytre-Hauge, Sigmund ; Hoivik, Erling A ; Husby, Jenny A ; Tangen, Ingvild L ; Trovik, Jone ; Halle, Mari K ; Woie, Kathrine ; Bjørge, Line ; Bjørnerud, Atle ; Salvesen, Helga B ; Werner, Henrica M J ; Krakstad, Camilla ; Haldorsen, Ingfrid S

Oncotarget, 2016-10, Vol.7 (43), p.69844-69856

United States: Impact Journals LLC

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4
Identifying menstrual migraine– improving the diagnostic criteria using a statistical method
Identifying menstrual migraine– improving the diagnostic criteria using a statistical method
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Identifying menstrual migraine– improving the diagnostic criteria using a statistical method

Barra, Mathias ; Dahl, Fredrik A. ; MacGregor, E. Anne ; Vetvik, Kjersti Grøtta

Journal of headache and pain, 2019-09, Vol.20 (1), p.95-95, Article 95 [Periódico revisado por pares]

Milan: Springer Milan

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