SHALLOW LEARNING MODEL FOR DIAGNOSING NEURO MUSCULAR DISORDER FROM SPLICING VARIANTS

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Title:	SHALLOW LEARNING MODEL FOR DIAGNOSING NEURO MUSCULAR DISORDER FROM SPLICING VARIANTS
Authors:	Sathyavikasini, Kalimuthu Vijaya, Vijayakumar
Keywords:	Machine learning Descriptors Disease Identification
Issue Date:	7-Aug-2017
Publisher:	Emerald Publishing Limited
Abstract:	Diagnosing genetic neuromuscular disorder such as muscular dystrophy is complicated when the imperfection occurs while splicing. This paper aims in predicting the type of muscular dystrophy from the gene sequences by extracting the well-defined descriptors related to splicing mutations. An automatic model is built to classify the disease through pattern recognition techniques coded in python using scikit-learn framework.
URI:	https://www.emerald.com/insight/content/doi/10.1108/WJE-09-2016-0075/full/html
Appears in Collections:	2.Article (26)

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