microarray data


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microarray data

The information obtained from microarray technology.
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As microarray technology has been developed for more than a decade, and the analytic methodology has been mature, we did not conduct the real time PCR for the verification of the bone relevant genes of microarray data from the sfx mice and their control mice.
As for the static expression data, we employed lung cancer microarray data obtained by Beer et al.
Verification of Microarray Data. The microarray gene expression data were verified by quantitative RT-PCR.
[10] Hong JH and Cho SB (2006), The classification of cancer based on DNA microarray data that uses diverse ensemble genetic programming, Artif.
We have performed experiments on different microarray data sets but in each run, it terminates with many genes selected.
In addition, it is not the intention of this manuscript to imply that microarray data analysis can alone provide an accurate diagnosis of cancer; a great deal of information must be considered before arriving at such a conclusion.
When microarray results are followed by a second assay to detect gene expression, for example, real-time PCR, respondents from most sectors indicated that 60-89% of the microarray data are confirmed.
To understand the biological implications of microarray data, functional annotation of differentially expressed genes was performed using DAVID, including GO and pathway enrichment analysis.
Feature extraction, is one of the most important technique used in analysis and interpretation of microarray data, it is sectioned into supervised and unsupervised machine learning methods.
After extensive analysis of microarray data, one needs to annotate Affymetrix IDs for its significance.
The main reason of microarray data classification is to create a classifier to classify new data and predict the future trend of data [4].