کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
403734 677327 2012 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Hybrid method for the analysis of time series gene expression data
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Hybrid method for the analysis of time series gene expression data
چکیده انگلیسی

Time series analysis plays an increasingly important role in the study of gene expression data. Some problems, such as a large amount of noise and a small number of replicates, are computational challenges in time series expression data analysis. This paper proposes a hybrid method for analyzing time series gene expression data (HMTS). In the HMTS method, we employ a combination of K-means clustering, regression analysis and piecewise polynomial curve fitting. The K-means clustering procedure is used to divide noisy time series into different clusters, and regression analysis is used to delete outliers according to different clusters. All time series data are divided into multiple segmentations, and polynomial curve fitting is used to fit all segmentation data. The HMTS method can obtain good estimates, especially when there is noise in the data.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 35, November 2012, Pages 14–20
نویسندگان
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