Framework of Classification with Microarray data Prediction Cancer Using Gene Express

Author : Sanku Rajendra Kumar, Dr. Anil Kumar

Classification of cancer based on gene expression has provided insight into possible treatment strategies. Analysis of gene expression is important in many fields of biological research in order to retrieve the required information. It provides accurate prediction providing better treatment to the patients. One of major challenges is to discover how to extract useful information from huge dataset. A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were used for quantitative expression measurements of the corresponding genes. Because of the small format and high density of the arrays. Cancer classification based on microarray has become a popular research topic in bioinformatics, which can be used to detect subtypes of cancers and produce therapies. Gene selection may provide insights into understanding the underlying mechanism of a specific biological phenomenon. Also, such information can be useful for designing less expensive experiments by targeting only a handful of genes. Finally, incorporating diverse types of genomic data (e.g., protein-protein interaction data and gene expression) increase the prediction accuracy as compared to using gene expression.

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