International Journal of Advances in Science, Engineering and Technology(IJASEAT)
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Volume-7,Issue-3  ( Jul, 2019 )
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Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
  Journal Paper

Paper Title
A Hybrid Approach Towards Classification Of Schizophrenia Microarray Data Along With Extraction With The Most Responsible Genes For The Disease

Analysis of microarray data for determination of the genes which are responsible for any genetic disease need effective computational techniques. As the human body consists of thousands of genes, the microarray data containing the information of the genes are tremendously huge. In this paper, we have presented a combined approach for revealing the gene pattern which may be associated with even a quite poor prognosis Schizophrenia disease. We have filtered the dataset using Gabor filter and the filtered output is then passed to a random forest classifier. The maximum achievable accuracy attained here for the diagnosis purpose is quite satisfactory. Also the gene pattern has been verified from DAVID ontological website where most of the genes extracted computationally are really associated with Schizophrenia Disease. Keywords— Schizophrenia Disease; Microarray Data;Gene;Gene Signature;Disease Diagnosis.

Author - Daphne Kordorwar, Paras Pokhrel, Goutam Saha

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| Published on 2016-02-01
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