Comparative Study on Gene Expression for Detecting Diseases Using Optimized Algorithm. (2nd January 2017)

• Record Type: Journal Article
• Authors: Sumitha, J.; Devi, T.; Ravi, D.
• Is Part Of: International journal of human genetics. Volume 17:Number 1(2017)
• Page Start: 38
• Page End: 42
• Publication Date: 2017-01-02
• Subjects: Breast Cancer -- Classification -- Confusion Matrix -- Micro-array Gene Expression Data; Human genetics -- Periodicals; 599.935
• DOI: 10.1080/09723757.2017.1305722
• Languages: English
• ISSNs: 0972-3757

Abstract

ABSTRACT: The main objective is to detect the disease-causing gene from microarray data and predict the results from the gene expression value. Many computer-assisted algorithms developed to predict the characteristic of a gene is done using machine learning and other bio-inspired algorithms. In this paper, seven works are proposed and compared to estimate the efficiency. The Support Vector Machine (SVM) optimized neuro-expert algorithm is developed to optimize these predictive results of both machine learning and bio-inspired algorithms and proven its effectiveness and efficiency in detecting the disease-causing gene than ever before.