Abstract
Background: The pandemic of metabolic disorders is accelerating in the urbanized world posing huge burden to healthand economy. The key pioneer to most of the metabolic disorders is Diabetes Mellitus. A newly discovered form of diabetes is MaturityOnset Diabetes of the Young (MODY). MODY is a monogenic form of diabetes. It is inherited as autosomal dominant disorder. Till to date11 different MODY genes have been reported. Objective: This study aims to discover subgroups from the biological text documentsrelated to these genes in public domain database. Data Source: The data set was obtained from PubMed. Period: September-December,2011. Materials and Methodology: APRIORI-SD subgroup discovery algorithm is used for the task of discovering subgroups. A wellknown association rule learning algorithm APRIORI is first modified into classification rule learning algorithm APRIORI-C. APRIORI-Calgorithm generates the rule from the discretized dataset with the minimum support set to 0.42% with no confidence threshold. Total 580rules are generated at the given support. APRIOIR-C is further modified by making adaptation into APRIORI-SD. Results: Experimentalresults demonstrate that APRIORI discovers the substantially smaller rule sets; each rule has higher support and significance. The rulesthat are obtained by APRIORI-C are ordered by weighted relative accuracy. Conclusion: Only first 66 rules are ordered as they cover therelation between all the 11 MODY genes with each other. These 66 rules are further organized into 11 different subgroups. The evaluationof obtained results from literature shows that APRIORI-SD is a competitive subgroup discovery algorithm. All the association amonggenes proved to be true.
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