کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
2822765 1161318 2008 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Gene Expression Data Classification Using Consensus Independent Component Analysis
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی ژنتیک
پیش نمایش صفحه اول مقاله
Gene Expression Data Classification Using Consensus Independent Component Analysis
چکیده انگلیسی
We propose a new method for tumor classification from gene expression data, which mainly contains three steps. Firstly, the original DNA microarray gene expression data are modeled by independent component analysis (ICA). Secondly, the most discriminant eigenassays extracted by ICA are selected by the sequential floating forward selection technique. Finally, support vector machine is used to classify the modeling data. To show the validity of the proposed method, we applied it to classify three DNA microarray datasets involving various human normal and tumor tissue samples. The experimental results show that the method is efficient and feasible.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Genomics, Proteomics & Bioinformatics - Volume 6, Issue 2, 2008, Pages 74-82
نویسندگان
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