Search Results - gene expression microarray data clustering

Incorporating gene ontology into fuzzy relational clustering of microarray gene expression data by Paul, Animesh Kumar, Shill, Pintu Chandra

“… (Saccharomyces cerevisiae) expression profiles datasets (Eisen and Dream5 yeast datasets).•The proposed clustering method helps to disclose the unknown functions of the genes…”
Get full text

Incorporating gene functions as priors in model-based clustering of microarray gene expression data by Pan, Wei

“…Motivation: Cluster analysis of gene expression profiles has been widely applied to clustering genes for gene function discovery…”
Get full text

Hybrid Genetic Algorithm and Simulated Annealing for Clustering Microarray Gene Expression data by Pandi, M, Sivakumar, T, Senthil Madasamy, N, Sadhasivam, N

“… The gene expression studies generate large amount of data. These data, referred to as the gene expression matrix, represent the expression levels for thousands of genes recorded at a few time instances…”
Get full text

Clustering by fast search and merge of local density peaks for gene expression microarray data by Mehmood, Rashid, El-Ashram, Saeed, Bie, Rongfang, Dawood, Hussain, Kos, Anton

“…Clustering is an unsupervised approach to classify elements based on their similarity, and it is used to find the intrinsic patterns of data…”
Get full text

Clustering microarray gene expression data using weighted Chinese restaurant process by Qin, Zhaohui S.

“…Motivation: Clustering microarray gene expression data is a powerful tool for elucidating co-regulatory relationships among genes…”
Get full text

Proximity Measures for Clustering Gene Expression Microarray Data: A Validation Methodology and a Comparative Analysis by Jaskowiak, Pablo A., Campello, Ricardo J. G. B., Costa, Ivan G.

“…Cluster analysis is usually the first step adopted to unveil information from gene expression microarray data…”
Get full text

Model-based clustering of microarray expression data via latent Gaussian mixture models by McNicholas, Paul D., Murphy, Thomas Brendan

“…Motivation: In recent years, work has been carried out on clustering gene expression microarray data…”
Get full text

Comparisons and validation of statistical clustering techniques for microarray gene expression data by Datta, Susmita, Datta, Somnath

“…Motivation: With the advent of microarray chip technology, large data sets are emerging containing the simultaneous expression levels of thousands of genes at various time points during a biological process…”
Get full text

Regulation and functional roles revealed by clustering of microarray expression data of Escherichia coli genes by Sánchez-Pérez, Mishael, Peralta, Humberto, Cecilia Ishida-Guitierrez, M, Santos-Zavaleta, Alberto, Martínez-Flores, Irma, Tavares-Carreon, Faviola, Ovando-Vázquez, Cesaré

“… Microarray data can be used to identify co-expressed genes that may be involved in the same biological process…”
Get full text

Incorporating biological knowledge into distance-based clustering analysis of microarray gene expression data by Huang, Desheng, Pan, Wei

“…Motivation: Because co-expressed genes are likely to share the same biological function, cluster analysis of gene expression profiles has been applied for gene function discovery…”
Get full text

An evolutionary clustering algorithm for gene expression microarray data analysis by Ma, P.C.H., Chan, K.C.C., Xin Yao, Chiu, D.K.Y.

“… For more effective clustering of gene expression microarray data, which is typically characterized by a lot of noise…”
Get full text

Digging for Significant Genes in Microarray Expression Data Based on Systematic Sampling and Hierarchal Clustering Algorithm by Mohammed, Nwayyin N

“… Therefore, in this chapter, we have analysed microarray expression data for obese and lean individuals…”
Get more information

Kernel hierarchical gene clustering from microarray expression data by Qin, Jie, Lewis, Darrin P., Noble, William Stafford

“…Motivation: Unsupervised analysis of microarray gene expression data attempts to find biologically significant patterns within a given collection of expression measurements…”
Get full text

R/BHC: fast Bayesian hierarchical clustering for microarray data by Savage, Richard S, Heller, Katherine, Xu, Yang, Ghahramani, Zoubin, Truman, William M, Grant, Murray, Denby, Katherine J, Wild, David L

“…Background Although the use of clustering methods has rapidly become one of the standard computational approaches in the literature of microarray gene expression data analysis, little attention…”
Get full text

Spatial clustering based gene selection for gene expression analysis in microarray data classification by Dhas, P. Edwin, S, Lalitha, Govindaraj, Annalakshmi, Jyoshna, B.

“… for workloads with noise. In these conditions, it is anticipated that the classification of the microarray gene expression database will have the necessary clustering property that may be utilized to emphasize the effects of the alterations…”
Get full text

Missing value imputation improves clustering and interpretation of gene expression microarray data by Tuikkala, Johannes, Elo, Laura L, Nevalainen, Olli S, Aittokallio, Tero

“…Background Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets…”
Get full text

Mixtures of common t-factor analyzers for clustering high-dimensional microarray data by Baek, Jangsun, McLachlan, Geoffrey J.

“…Motivation: Mixtures of factor analyzers enable model-based clustering to be undertaken for high-dimensional microarray data, where the number of observations n is small relative to the number of genes p…”
Get full text

TriRNSC: triclustering of gene expression microarray data using restricted neighbourhood search by Biswal, Bhawani Sankar, Patra, Sabyasachi, Mohapatra, Anjali, Vipsita, Swati

“… Clustering and biclustering of gene expression microarray data in the unsupervised domain are extremely important as their outcomes directly dominate healthcare research in many aspects…”
Get full text

Techniques for clustering gene expression data by Kerr, G., Ruskin, H.J., Crane, M., Doolan, P.

“…Many clustering techniques have been proposed for the analysis of gene expression data obtained from microarray experiments…”
Get full text

Clustering methods for microarray gene expression data by Belacel, Nabil, Wang, Qian, Cuperlovic-Culf, Miroslava

“… in microarray gene expression data analysis…”
Get more information