کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9748543 | 1493784 | 2005 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Optimisation of high performance liquid chromatography separation of neuroprotective peptides
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
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چکیده انگلیسی
The study of experimental design conjunction with artificial neural networks for optimisation of isocratic ion-pair reverse phase HPLC separation of neuroprotective peptides is reported. Different types of experimental designs (full-factorial, fractional) were studied as suitable input and output data sources for ANN training and examined on mixtures of humanin derivatives. The independent input variables were: composition of mobile phase, including its pH, and column temperature. In case of a simple mixture of two peptides, the retention time of the most retentive component and resolution were used as the dependent variables (outputs). In case of a complex mixture with unknown number of components, number of peaks, sum of resolutions and retention time of ultimate peak were considered as output variables. Fractional factorial experimental design has been proved to produce sufficient input data for ANN approximation and thus further allowed decreasing the number of experiments necessary for optimisation. After the optimal separation conditions were found, fractions with peptides were collected and their analysis using off-line matrix assisted laser desorption/ionisation time of flight mass spectrometry (MALDI-TOF-MS) was performed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Chromatography A - Volume 1096, Issues 1â2, 25 November 2005, Pages 50-57
Journal: Journal of Chromatography A - Volume 1096, Issues 1â2, 25 November 2005, Pages 50-57
نویسندگان
Klára Novotná, Jan HavliÅ¡, Josef Havel,