objective(s): microarrays are potential analyzing tools for genomics and proteomics researches, which is in needed of suitable substrate for coating and also hybridization of biomolecules.   materials and methods: in this research, a thin film of oxidized agarose was prepared on the glass slides which previously coated with poly-l-lysine (pll). some of the aldehyde groups of the activated agaro...

DNA microarray technology has now made it possible to monitor the expression levels of thousands of genes simultaneously during important biological processes and across collections of related samples. Usually, gene expression matrix has several particular macroscopic phenotypes of samples. However, this matrix has few samples, and vast amounts of genes. This feature makes it difficult to class...

The Genome Project has revitalized exploration in biological research. DNA microarray technology allows us to probe the genome and monitor gene expression levels on a genomic scale. The high throughput data generated by this technology promise to enhance fundamental understanding of processes on the molecular level and may prove useful in medical diagnosis, treatment and drug design. Analysis o...

DNA microarray technology produces large amounts of data. For data mining of these datasets, background information on genes can be helpful. Unfortunately most information is stored in free text. Here, we present an approach to use this information for DNA microarray data mining.

UNLABELLED The microarray gene expression markup language (MAGE-ML) is a widely used XML (eXtensible Markup Language) standard for describing and exchanging information about microarray experiments. It can describe microarray designs, microarray experiment designs, gene expression data and data analysis results. We describe RMAGEML, a new Bioconductor package that provides a link between cDNA m...

Microarray data should be interpreted in the context of existing biological knowledge. Here we present integrated analysis of microarray data and gene function classification data using homogeneity analysis. Homogeneity analysis is a graphical multivariate statistical method for analyzing categorical data. It converts categorical data into graphical display. By simultaneously quantifying the mi...

in this paper, we propose a new gene selection algorithm based on shuffled frog leaping algorithm that is called sfla-fs. the proposed algorithm is used for improving cancer classification accuracy. most of the biological datasets such as cancer datasets have a large number of genes and few samples. however, most of these genes are not usable in some tasks for example in cancer classification. ...

BACKGROUND Limited replicative capacity is a defining characteristic of most normal human cells and culminates in senescence, an arrested state in which cells remain viable but display an altered pattern of gene and protein expression. To survey widely the alterations in gene expression, we have developed a DNA microarray analysis system that contains genes previously reported to be involved in...

Microarrays are one of the latest breakthroughs in experimental molecular biology, that allow monitoring of gene expression of tens of thousands of genes in parallel. Knowledge about expression levels of all or a big subset of genes from different cells may help us in almost every field of society. Amongst those fields are diagnosing diseases or finding drugs to cure them. Analysis and handling...

DNA microarray is an innovative technology for obtaining information on gene function. Because it is a high-throughput method, computational tools are essential in data analysis and mining to extract the knowledge from experimental results. Filtering procedures and statistical approaches are frequently combined to identify differentially expressed genes. However, obtaining a list of differentia...