Analysis of gene expression data: clustering and beyond
نویسندگان
چکیده
منابع مشابه
the clustering and classification data mining techniques in insurance fraud detection:the case of iranian car insurance
با توجه به گسترش روز افزون تقلب در حوزه بیمه به خصوص در بخش بیمه اتومبیل و تبعات منفی آن برای شرکت های بیمه، به کارگیری روش های مناسب و کارآمد به منظور شناسایی و کشف تقلب در این حوزه امری ضروری است. درک الگوی موجود در داده های مربوط به مطالبات گزارش شده گذشته می تواند در کشف واقعی یا غیرواقعی بودن ادعای خسارت، مفید باشد. یکی از متداول ترین و پرکاربردترین راه های کشف الگوی داده ها استفاده از ر...
Evaluation and optimization of clustering in gene expression data analysis
MOTIVATION A measurement of cluster quality is needed to choose potential clusters of genes that contain biologically relevant patterns of gene expression. This is strongly desirable when a large number of gene expression profiles have to be analyzed and proper clusters of genes need to be identified for further analysis, such as the search for meaningful patterns, identification of gene functi...
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DNA microarray technology has now made it possible to monitor the expression levels of thousands of genes simultaneously during important biological processes and across collections of related samples. Usually, gene expression matrix has several particular macroscopic phenotypes of samples. However, this matrix has few samples, and vast amounts of genes. This feature makes it difficult to class...
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Microarray is used to generate large amount of gene expression data and observing the differences among gene expression levels. Gene expression time series data represents the trend of gene behaviors. Clustering is a popular analysis for gene expression time series data. Genes in the same cluster have similar behavior. Cluster analysis helps people investigate the relativity among genes. We pro...
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Preprint submitted to Elsevier Science 29 April 2003 A clustering method based on recursive bisection is introduced for analyzing microarray gene expression data. Either or both dimensions for the genes and the samples of a given microarray dataset can be classi£ed in an unsupervised fashion. Alternatively, if certain prior knowledge of the genes or samples is available, a supervised version of...
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ژورنال
عنوان ژورنال: Nature Genetics
سال: 1999
ISSN: 1061-4036,1546-1718
DOI: 10.1038/14430