One of the purposes of several statistical techniques is to reduce random noise and improve the quality of the data. In microarray experiments random noise can introduce errors that affect gene expression measurements and obscure the interesting biological variation. In recent years, several authors have described common techniques to minimize the effects of systematic variation incorporated into microarray data at different stages of the manufacturing process (see for example [3] and [4]). There is though a particular step in the microarray data analysis workflow that is and that be performed the image of raw data
Introduction Microarray hybridisation experiments are used to measure concentrations of many differ...
Abstract—In oligonucleotide microarray experiments, noise is a challenging problem, as biologists no...
DNA microarrays are strikingly efficient tools for analysing gene expression for large sets of genes...
This paper introduces a novel method for processing spotted microarray images, inspired from image r...
Preprocessing of microarray data involves the necessary steps of background correction, normalizatio...
In this paper, fluorescent microarray images and various analysis techniques are described to improv...
In this paper, fluorescent microarray images and various analysis techniques are described to improv...
The quality of gene expression microarray data has improved dramatically since the first arrays were...
Spotted cDNA microarray data analysis suffers from various problems such as noise from a variety of ...
2-dye microarrays are an increasingly common, but typically noisy, method of identifying gene expres...
The use of a constant fold-change to determine significant changes in gene expression has been widel...
There is a lot of systematic and specific variability in microarray experiments, this variability af...
The advent of microarray technology has significantly changed the way we can quantitatively measure ...
Due to the nature of microarray experiments, gene expression levels across and through slide channel...
The random measurement or technological variation of an Affymetrix high-density oligonucleotide micr...
Introduction Microarray hybridisation experiments are used to measure concentrations of many differ...
Abstract—In oligonucleotide microarray experiments, noise is a challenging problem, as biologists no...
DNA microarrays are strikingly efficient tools for analysing gene expression for large sets of genes...
This paper introduces a novel method for processing spotted microarray images, inspired from image r...
Preprocessing of microarray data involves the necessary steps of background correction, normalizatio...
In this paper, fluorescent microarray images and various analysis techniques are described to improv...
In this paper, fluorescent microarray images and various analysis techniques are described to improv...
The quality of gene expression microarray data has improved dramatically since the first arrays were...
Spotted cDNA microarray data analysis suffers from various problems such as noise from a variety of ...
2-dye microarrays are an increasingly common, but typically noisy, method of identifying gene expres...
The use of a constant fold-change to determine significant changes in gene expression has been widel...
There is a lot of systematic and specific variability in microarray experiments, this variability af...
The advent of microarray technology has significantly changed the way we can quantitatively measure ...
Due to the nature of microarray experiments, gene expression levels across and through slide channel...
The random measurement or technological variation of an Affymetrix high-density oligonucleotide micr...
Introduction Microarray hybridisation experiments are used to measure concentrations of many differ...
Abstract—In oligonucleotide microarray experiments, noise is a challenging problem, as biologists no...
DNA microarrays are strikingly efficient tools for analysing gene expression for large sets of genes...