Results 1 to 10 of about 544,008 (293)

Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization.

Molecular Biology of the Cell, 1998
P. Spellman, G. Sherlock, Michael Ruogu Zhang, V. Iyer, Klaus E. Anders, M. Eisen, P. Brown, D. Botstein, B. Futcher   +8 more
semanticscholar   +3 more sources

Support vector machine classification and validation of cancer tissue samples using microarray expression data [PDF]

Bioinform., 2000
T. Furey, N. Cristianini, Nigel P. Duffy, D. Bednarski, M. Schummer, D. Haussler   +5 more
semanticscholar   +2 more sources

Knowledge-based analysis of microarray gene expression data by using support vector machines. [PDF]

Proceedings of the National Academy of Sciences of the United States of America, 2000
M. S. Brown, W. Grundy, D. Lin, N. Cristianini, C. Sugnet, T. Furey, M. Ares, D. Haussler   +7 more
semanticscholar   +2 more sources

limma powers differential expression analyses for RNA-sequencing and microarray studies

Nucleic Acids Research, 2015
limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the ...
Matthew E. Ritchie, B. Phipson, Diabetes-Ling Wu, Yifang Hu, C. Law, Wei Shi, G. Smyth   +6 more
semanticscholar   +1 more source

GSVA: gene set variation analysis for microarray and RNA-Seq data

BMC Bioinformatics, 2013
Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary.
Sonja Hänzelmann, R. Castelo, J. Guinney   +2 more
semanticscholar   +1 more source

TM4: a free, open-source system for microarray data management and analysis.

BioTechniques, 2003
White1, J. Li1, W. Liang1, N. Bhagabati1, J. Braisted1, M. Klapa1, T. Currier1, M. Thiagarajan1, A. Sturn1, M. Snuffin2, A. Rezantsev2, D. Popov2, A. Ryltsov2, E. Kostukovich2, I. Borisovsky2, Z. Liu3, A. Vinsavich3, V. Trush3, and J. Quackenbush1,4 1The
A. Saeed, V. Sharov, J. White, J. Li, W. Liang, N. Bhagabati, J. Braisted, M. Kłapa, T. Currier, M. Thiagarajan, A. Sturn, M. Snuffin, A. Rezantsev, D. Popov, A. Ryltsov, E. Kostukovich, I. Borisovsky, Z. Liu, A. Vinsavich, V. Trush, John Quackenbush   +20 more
semanticscholar   +1 more source

A Review of Feature Selection and Feature Extraction Methods Applied on Microarray Data

Adv. Bioinformatics, 2015
We summarise various ways of performing dimensionality reduction on high-dimensional microarray data. Many different feature selection and feature extraction methods exist and they are being widely used.
Zena M. Hira, D. Gillies
semanticscholar   +1 more source

Comparison of RNA-Seq and Microarray Gene Expression Platforms for the Toxicogenomic Evaluation of Liver From Short-Term Rat Toxicity Studies

Frontiers in Genetics, 2019
Gene expression profiling is a useful tool to predict and interrogate mechanisms of toxicity. RNA-Seq technology has emerged as an attractive alternative to traditional microarray platforms for conducting transcriptional profiling.
Mohan S. Rao, T. V. Van Vleet, R. Ciurlionis, W. Buck, S. Mittelstadt, E. Blomme, M. Liguori   +6 more
semanticscholar   +1 more source

A Survey on Hybrid Feature Selection Methods in Microarray Gene Expression Data for Cancer Classification

IEEE Access, 2019
The emergence of DNA Microarray technology has enabled researchers to analyze the expression level of thousands of genes simultaneously. The Microarray data analysis is the process of finding the most informative genes as well as remove redundant and ...
Nada Almugren, Hala M. Alshamlan
semanticscholar   +1 more source

Comparison of RNA-Seq and Microarray in Transcriptome Profiling of Activated T Cells

PLoS ONE, 2014
To demonstrate the benefits of RNA-Seq over microarray in transcriptome profiling, both RNA-Seq and microarray analyses were performed on RNA samples from a human T cell activation experiment.
Shanrong Zhao, W. Fung-Leung, A. Bittner, K. Ngo, Xuejun Liu   +4 more
semanticscholar   +1 more source