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Paper Details

Multi-omic machine learning predictor of breast cancer therapy response.
Nature
145
2022
Breast cancers, HER2, T, T-cell dysfunction, breast cancer, breast tumours, cancers, malignant, malignant cells, patients, tumour
Author NameAffiliation
Stephen-John SammutCancer Research UK Cambridge Institute, University of Cambridge
Stephen-John SammutCambridge Experimental Cancer Medicine Centre (ECMC) and NIHR Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust
Stephen-John SammutUniversity of Cambridge
Janet A DunnWarwick Clinical Trials Unit, University of Warwick
John M S BartlettEdinburgh Cancer Research Centre, Western General Hospital
John M S BartlettOntario Institute for Cancer Research
John M S BartlettUniversity of Toronto
Paul D P PharoahCambridge Experimental Cancer Medicine Centre (ECMC) and NIHR Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust
Paul D P PharoahUniversity of Cambridge
Paul D P PharoahCambridge Experimental Cancer Medicine Centre (ECMC) and NIHR Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust
Paul D P PharoahUniversity of Cambridge
Florian MarkowetzCancer Research UK Cambridge Institute, University of Cambridge
Florian MarkowetzCancer Research UK Cambridge Institute, University of Cambridge
Oscar M RuedaCancer Research UK Cambridge Institute, University of Cambridge
Oscar M RuedaUniversity of Cambridge
Carlos CaldasCancer Research UK Cambridge Institute, University of Cambridge
Carlos CaldasUniversity of Cambridge
Carlos CaldasCambridge Experimental Cancer Medicine Centre (ECMC) and NIHR Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust
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