کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7612571 1493564 2014 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
What can go wrong at the data normalization step for identification of biomarkers?
ترجمه فارسی عنوان
چه چیزی می تواند در مرحله نرمال سازی داده ها برای شناسایی بیومارکرها اشتباه باشد؟
کلمات کلیدی
روش نسبت ورود به سیستم، اثر اندازه، اثر شکل، اثر انگشت تجزیه و تحلیل اطلاعات ترکیب
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی
Our study focuses on the removal of the so-called size effect, related to a different sample volume and/or concentration. This effect is associated with many types of instrumental signals, particularly with those originating from HPLC-DAD, LC-MS, and UPLC-MS. These signals do not carry any absolute information about the sample components. If the data comparison has to be performed based on sample fingerprints, then the size effect is undesired, and the shape effect is of main interest. With “shape”, we refer to data information which is contained in the ratios between the variables. So far, different normalization methods have been applied to the removal of size effect. In our study, the performance of popular normalization methods is compared with those of the CODA (Compositional Data Analysis) methods, relying on log-ratio transformations, and the performance is evaluated through the prism of proper identification of biomarkers.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Chromatography A - Volume 1362, 3 October 2014, Pages 194-205
نویسندگان
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