Advanced Analysis of Gene Expression Microarray DataWorld Scientific, 2006 - 339페이지 This book focuses on the development and application of the latest advanced data mining, machine learning, and visualization techniques for the identification of interesting, significant, and novel patterns in gene expression microarray data.Biomedical researchers will find this book invaluable for learning the cutting-edge methods for analyzing gene expression microarray data. Specifically, the coverage includes the following state-of-the-art methods: ? Gene-based analysis: the latest novel clustering algorithms to identify co-expressed genes and coherent patterns in gene expression microarray data sets? Sample-based analysis: supervised and unsupervised methods for the reduction of the gene dimensionality to select significant genes. A series of approaches to disease classification and discovery are also described? Pattern-based analysis: methods for ascertaining the relationship between (subsets of) genes and (subsets of) samples. Various novel pattern-based clustering algorithms to find the coherent patterns embedded in the sub-attribute spaces are discussed? Visualization tools: various methods for gene expression data visualization. The visualization process is intended to transform the gene expression data set from high-dimensional space into a more easily understood two- or three-dimensional space |
기타 출판본 - 모두 보기
자주 나오는 단어 및 구문
Affymetrix amino acid analysis approach array biclusters biological box plot cDNA cell classification clustering algorithms co-expressed genes coherent gene cluster coherent sample set contains corresponding Cy3 and Cy5 data objects data point data set density differentially expressed dimensional discrete-time Fourier transform distribution DNA microarray Euclidean distance expression data set expression levels expression patterns expression profiles Expression Value Figure function gene expression data gene g gene groups genes and samples genome histogram identify indicates informative genes interaction itemsets iteration K-means algorithm log ratio mapping matrix maximal coherent gene maximal coherent sample measure method microarray data set microarray experiment mining molecule mRNA multiple node normal null hypothesis number of clusters number of genes p-value pair parallel coordinates parameters phenotype structure proteins pruning reference partition represents Section selected sequence signal significant similarity statistical subset of genes t-statistic techniques threshold virtual genes visualization