Machine Learning for the Identification of the Dna Variations for Diseases Diagnosis
نویسنده
چکیده
In this paper we give an overview of a basic computational haplotype analysis, including the pairwaise association with the use of clustering, and tagged prediction (using Bayesian networks). Moreover, we present several machine learning methods in order to explore the association between human genetic variations and diseases. These methods include the clustering of SNPs based on some similarity measures and selecting of one SNP per cluster, the support vector machines, etc. The presented machine learning methods can help to generate a plausible hypothesis for some classification systems.
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