Predicting Muscular Dystrophy through Genetic testing - A Study

Sathyavikasini K¹, Vijaya M S²

¹Research scholar, ²Associate professor
PSGR Krishnammal College for Women, Coimbatore.

Abstract

A pathologic condition impairs the normal function or structure of an organ in human beings. In the current genomic era, the identification of the disease is paramount. Genetic diseases are caused by the abnormalities in the inherited genes. Muscular dystrophy is an inherited genetic disorder that is rooted by the huge number of sequence variants found in large sets of genes. There are about 9 major forms in muscular dystrophy and a better understanding is needed to predict this genetic disease. The mutation in the genes causes most of these disorders. There are currently no effective treatments to halt the muscle breakdown in muscular dystrophies. A new approach is to be designed to predict the muscular dystrophy disease subtypes effectively. As the growth of biological data increases, storage and analysis become incredible this in turn increases the processing time and cost efficiency. This paves the way for challenges in computing. The objective of machine learning is to dig out valuable information from a corpus of data by building good probabilistic models. In this paper, a preface to muscular dystrophy, traditional and innovative approaches involved in identifying this disease are discussed.

Keywords

• Genes, DNA, Mutation, Codon, Genetic disease, Amino acids, Allele

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Cite this Article as Follows

Sathyavikasini K, Vijaya M S. "Predicting Muscular Dystrophy through Genetic testing ‐ A Study." International Conference on Innovative Trends in Electronics Communication and Applications (2015): 65-71. Print.