A Framework for Efficient N-Way Interaction Testing in Case/Control Studies With Categorical Data

<italic>Goal:</italic> Most common diseases are influenced by multiple gene interactions and interactions with the environment. Performing an exhaustive search to identify such interactions is computationally expensive and needs to address the multiple testing problem. A four-step framew...

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Autores principales:	Aristos Aristodimou, Athos Antoniades, Efthimios Dardiotis, Eleni Loizidou, George Spyrou, Christina Votsi, Christodoulou Kyproula, Marios Pantzaris, Nikolaos Grigoriadis, Georgios Hadjigeorgiou, Theodoros Kyriakides, Constantinos Pattichi
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Clustering Epistasis Feature Selection Interaction Testing Machine Learning Computer applications to medicine. Medical informatics R858-859.7 Medical technology R855-855.5
Acceso en línea:	https://doaj.org/article/37424223ba2649ab913818a0b0e64cf5
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A Framework for Efficient N-Way Interaction Testing in Case/Control Studies With Categorical Data

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