Techniques for clustering gene expression data

Techniques for clustering gene expression data

Many clustering techniques have been proposed for the analysis of gene expression data obtained from microarray experiments. However, choice of suitable method(s) for a given experimental dataset is not straightforward. Common approaches do not translate well and fail to take account of the data profile. This review paper surveys state of the art applications which recognise these limitations a...

Comparative Study of Clustering Techniques for Gene Expression Microarray Data

Scientists can now monitor on a genomic scale the patterns of gene expression under varying environmental conditions. With this rapidly growing wealth of information comes the need for organizing and analyzing the data. One natural approach is to group together genes with similar patterns of expression. Several approaches have suggested various alternatives for similarity metrics and clustering...

Parameterless Clustering Techniques for Gene Expression Analysis

In recent years, clustering analysis has even become a valuable and useful tool for insilico analysis of microarray or gene expression data. Although a number of clustering methods have been proposed, they are confronted with difficulties in meeting the requirements of automation, high quality, and high efficiency at the same time. In this chapter, we discuss the issue of parameterless clusteri...

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...

Effective Clustering Algorithms for Gene Expression Data