Results 21 to 30 of about 31,256,270 (297)

Edge-weighting of gene expression graphs [PDF]

, 2009
In recent years, considerable research efforts have been directed to micro-array technologies and their role in providing simultaneous information on expression profiles for thousands of genes.
Kerr, Gráinne, Crane, Martin, DIMITRI PERRIN, HEATHER J. RUSKIN, Ruskin, Heather J., Perrin, Dimitri, MARTIN CRANE, GRAINNE KERR, Ruskin, Heather J   +8 more
core   +3 more sources

Fuzzy clustering of time series gene expression data with cubic-spline [PDF]

, 2013
Data clustering techniques have been applied to ex- tract information from gene expression data for two decades. A large volume of novel clustering algorithms have been developed and achieved great success.
Ali, Akhtar, Wang, Yu, Angelova, Maia
core   +1 more source

Gene expression data analysis

Microbes and Infection, 2000
Microarrays are one of the latest breakthroughs in experimental molecular biology, which allow monitoring of gene expression for tens of thousands of genes in parallel and are already producing huge amounts of valuable data. Analysis and handling of such data is becoming one of the major bottlenecks in the utilization of the technology.
Brazma, Alvis, Vilo, Jaak
openaire   +3 more sources

Categorical Data Analysis for High-Dimensional Sparse Gene Expression Data

BioTech, 2023
Categorical data analysis becomes challenging when high-dimensional sparse covariates are involved, which is often the case for omics data. We introduce a statistical procedure based on multinomial logistic regression analysis for such scenarios ...
Niloufar Dousti Mousavi, Hani Aldirawi, Jie Yang   +2 more
doaj   +1 more source

Gene set analysis for longitudinal gene expression data

BMC Bioinformatics, 2011
Background Gene set analysis (GSA) has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations.
Piepho Hans-Peter, Harrar Solomon W, Bathke Arne C, Wang Haiyan, Zhang Ke, Deng Youping   +5 more
doaj   +1 more source

A Microarray Data Pre-processing Method for Cancer Classification

JOIV: International Journal on Informatics Visualization, 2022
The development of microarray technology has led to significant improvements and research in various fields. With the help of machine learning techniques and statistical methods, it is now possible to organize, analyze, and interpret large amounts of ...
Tay Xin Hui, Shahreen Kasim, Mohd Farhan Md Fudzee, Zubaile Abdullah, Rohayanti Hassan, Aldo Erianda   +5 more
doaj   +1 more source

CoXpress: differential co-expression in gene expression data

BMC Bioinformatics, 2006
Background Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find groups of genes that behave similarly across a dataset.
Watson Michael
doaj   +1 more source

Consensus clustering and functional interpretation of gene-expression data [PDF]

, 2004
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters.
Liu, X, Orengo, Christine, Martin, N, Kellam, P., Paul Kellam, Liu, X., Swift, Stephen, Swift, S, Orengo, C.A., Tucker, Allan, Tucker, A., Tucker, A, Liu, XH, Allan Tucker, Vinciotti, Veronica, Christine Orengo, Veronica Vinciotti, Vinciotti, V., Xiaohui Liu, Swift, S., Kellam, P, Liu, Xiaohui, Vinciotti, V, Stephen Swift, Kellam, Paul, Orengo, C, Martin, Nigel, Nigel Martin   +27 more
core   +1 more source

Bi-dimensional principal gene feature selection from big gene expression data

PLoS ONE, 2022
Gene expression sample data, which usually contains massive expression profiles of genes, is commonly used for disease related gene analysis. The selection of relevant genes from huge amount of genes is always a fundamental process in applications of ...
Xiaoqian Hou, Jingyu Hou, Guangyan Huang
doaj   +2 more sources

Gene expression data analysis using Hellinger correlation in weighted gene co-expression networks (WGCNA)

Computational and Structural Biotechnology Journal, 2022
Weighted gene co-expression network analysis (WGCNA) is used to detect clusters with highly correlated genes. Measurements of correlation most typically rely on linear relationships.
Tianjiao Zhang, Garry Wong
doaj   +1 more source