High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer.

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作者： Stefan,Enroth ^[1] ; Malin,Berggrund ^[1] ; Maria,Lycke ^[2] ; John,Broberg ^[3] ; Martin,Lundberg ^[3] ; Erika,Assarsson ^[3] ; Matts,Olovsson ^[4] ; Karin,Stålberg ^[4] ; Karin,Sundfeldt ^[2] ; Ulf,Gyllensten ^[1]

作者单位： 1Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Box 815, Uppsala University, SE-75108 Uppsala, Sweden. ^[1] 2Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, Gothenburg, Sweden. ^[2] OLINK Proteomics, Uppsala Science Park, SE-751 83 Uppsala, Sweden. ^[3] 4Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden. ^[4]

关键词 Diagnostic markers Machine learning Ovarian cancer

主题词年龄因素(Age Factors);老年人(Aged);队列研究(Cohort Studies);女(雌)性(Female);高通量筛选分析(High-Throughput Screening Assays);人类(Humans);中年人(Middle Aged);肿瘤分期(Neoplasm Staging);卵巢肿瘤(Ovarian Neoplasms);蛋白质组学(Proteomics);敏感性与特异性(Sensitivity and Specificity)

DOI 10.1038/s42003-019-0464-9

PMID 31240259

发布时间 2024-02-29

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准确一般字义偏差语意偏离译文作用小提交

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Communications biology

2019年2卷

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High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer.

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High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer.

Communications biology

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Communications biology

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