Distinguishing the serum metabolite profiles differences in breast cancer by gas chromatography mass spectrometry and random forest method
作者： Jian-Hua Huang , Liang Fu , Bin Li , Hua-Lin Xie , Xiaojuan Zhang
DOI: 10.1039/C5RA10130A
关键词: Potential biomarkers 、 Metabolomics 、 Serum samples 、 Gas chromatography–mass spectrometry 、 In patient 、 Metabolite 、 Oncology 、 Breast cancer 、 Medicine 、 Analytical chemistry 、 Random forest 、 Internal medicine
摘要: In this study, we proposed a metabolomics strategy to distinguish different metabolic characters of healthy controls, breast benign (BE) patients, and malignant (BC) patients by using the GC-MS random forest method (RF). current serum samples from BE BC were characterized GC-MS. Then, (RF) models established visually discriminate differences among three groups' metabolites profiles, further investigate progress cancer in based on these profiles. We successfully discovered between patients. And changes obviously visualized. The results suggested that combining profiling with is useful approach analyze screen potential biomarkers for exploring profiles cancer.
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