Boosting Multifactor Dimensionality Reduction Using Pre-evaluation
نویسندگان
چکیده
منابع مشابه
A roadmap to multifactor dimensionality reduction methods
Complex diseases are defined to be determined by multiple genetic and environmental factors alone as well as in interactions. To analyze interactions in genetic data, many statistical methods have been suggested, with most of them relying on statistical regression models. Given the known limitations of classical methods, approaches from the machine-learning community have also become attractive...
متن کاملIdentification of interactions using model-based multifactor dimensionality reduction
BACKGROUND Common complex traits may involve multiple genetic and environmental factors and their interactions. Many methods have been proposed to identify these interaction effects, among them several machine learning and data mining methods. These are attractive for identifying interactions because they do not rely on specific genetic model assumptions. To handle the computational burden aris...
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abstracts should not cite references, nor refer to figures or tables. The reference to Ritchie et al 2001 has been removed from the abstract on Page 2. Minor revisions (we can make these changes for you, although it will speed up publication of your manuscript if you do them while making the major changes above) Author Contributions: Please confirm that all authors read and approved the final m...
متن کاملNew evaluation measures for multifactor dimensionality reduction classifiers in gene-gene interaction analysis
MOTIVATION Gene-gene interactions are important contributors to complex biological traits. Multifactor dimensionality reduction (MDR) is a method to analyze gene-gene interactions and has been applied to many genetics studies of complex diseases. In order to identify the best interaction model associated with disease susceptibility, MDR classifiers corresponding to interaction models has been c...
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Gene-gene interaction (GGI) plays an important role in the causation of complex diseases, and its importance has now been well recognized through the findings of many successful genome-wide association studies (GWAS). Although many statistical methods have been introduced to address GGI analysis in GWAS, these methods have mainly focused on two-way interactions, rather than on high-order intera...
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ژورنال
عنوان ژورنال: ETRI Journal
سال: 2016
ISSN: 1225-6463
DOI: 10.4218/etrij.16.0114.0040