Abstract—Microarray technology is one of the important biotechnological means that allows to record the expression levels of thousands of genes simultaneously within a number of different samples. An important application of microarray gene expression data in functional genomics is to classify samples according to their gene expression profiles. Among the large amount of genes presented in gene expression data, only a small fraction of them is effective for performing a certain diagnostic test. Hence, one of the major tasks with the gene expr ....etc

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efficient and accurate discovery of patterns in sequence data set ppt ....etc

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Visualization of Microarray Data
Contents:
Introduction
Visualization Methods
Visualization Tools
Comparison between Tools
Experiments
Conclusion
Introduction
Microarray
Advancing with numerous applications in gene expression, genotyping, cell biology.
Helps researchers to
Learn more about diseases.
Study of Cancer.
Overview
Visualization of Microarray Data
Heat Maps
Dendrograms
TreeMaps
Scatter-Plots (2-D/3-D).
Box Plot
Clusterview and Treeview.
organize and analyze the data in ma ....etc

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Jini provides facilities for dealing with some of the Fallacies of Distributed Computing, problems of system evolution, resiliency, security and the dynamic assembly of service components. Code mobility is a core concept of the platform and provides many benefits including non-Protocol dependence. The Jini team at Sun Microsystems has always stated that Jini is not an acronym. Some have joked that it meant Jini Is Not Initials, but it's always been just Jini. The word Jini means the devil in Kiswahili; this is a loan from an Arabic word for ....etc

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Discriminative Learing and Recognition of Image set classes Using Canonical Correlation

Abstract:

Canonical angles or principle angle between the two dimensional sub-space.

Canonical angle is compared with the two main classical methods: parametric distribution based and non parametric sample based.

The classical linear discriminate analysis which we have to develop is to be maximizing the correlation with-in the class set and it has to minimize between the class-set.

Image set after transforming the discrimi ....etc

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#include
#include
#include
void main()
{
int loop,loop1,loop2,temp,temp1,flen;
char frame={'0'};
char comp={'0'};
char quat={'0'};
char generator={'1','1','0','0','0','0','0','0','1','0','1'};
clrscr();
printf( enter the frame:\n\t);
for(loop=0;loop<88;loop++)
{
frame=getch();
temp=frame;
if(temp!=13&&temp!=48&&temp!=49)
{
loop--;
continue;
}
putch(frame);
if(frame==13)
break;
}
flen=loop;
for(loop=0;loop<13;loop++)
{
if(loop comp[loo ....etc

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Automatic Gridding for DNA Microarray Image Using Image Projection Profile



Abstract

DNA microarray is powerful tool and widely used in many areas.
DNA microarray is produced from control and test tissue sample cDNAs, which
are labeled with two different fluorescent dyes. After hybridization using a laser
scanner, microarray images are obtained. Image analysis play an important role
in extracting fluorescence intensity from microarray image. First step ....etc

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Mining Microarray



ORIGIN OF MICROARRAY


-Many experiments on molecular biology since 1970

-Development of DNA sequencing

-Polymerase Chain Reaction (PCR)

WHAT IS MICROARRAY ?


-Ordered set of DNA molecule of known sequence

-May consists of few hundreds to hundred of thousands

-Individual feature in the array at precisely definite location of the substrate

-Identity of the DNA molecule never changes


IMPORTANCE OF MICROARRAY ....etc

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Hi,

Can anybody help me with the matlab code of Clustering the dataset using fuzzy k mean algorithm?

Regards,
Gowri
Hi,

Can anybody help me with the matlab code of Clustering the dataset using fuzzy C mean algorithm?

Regards,
Gowri ....etc

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i want rough set quick reduct code for matlab. ....etc

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