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• W2612641567 abstract "The majority of common diseases are influenced by multiple genetic and environmental factors such as Cancer. Even though uncovering the main causes of disease is deemed difficult due to the complexity of gene-gene and gene-environment interactions, major research efforts aim at identifying disease risk factors, especially genetic ones. Over the past decade, disease association studies have been used to uncover the susceptibility, aetiology and mechanisms of action pertaining to common diseases. In disease association studies, genetic data is analyzed in order to reveal the relationship between different types of variants, and a disease of interest. The ultimate goal of association studies is to facilitate susceptibility testing for disease prediction, early diagnosis and enhanced prognosis . Susceptibility testing and disease prediction are particularly important for diseases that can be prevented by diet, drugs or change in lifestyle. The discovered associations assist in understanding the molecular mechanisms influenced by the reported variants, and in identifying important risk factors. Current association studies suffer from several shortcomings. This report surveys the literature that addresses the shortcomings of current methods the identify genetic disease associations. In addition, it reviews the suggested solutions that either enhance some aspect of the methodologies, or complement them." @default.
• W2612641567 created "2017-05-19" @default.
• W2612641567 creator A5037989553 @default.
• W2612641567 date "2017-05-09" @default.
• W2612641567 modified "2023-09-27" @default.
• W2612641567 title "Increasing the Discovery Power and Confidence Levels of Disease Association Studies: A Survey." @default.
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• W2612641567 hasPublicationYear "2017" @default.
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