Impact of the Different Discretization Methods on Gene Expression Biclustering: Alzheimer Disease Progression Data as a Case Study

CARBALLIDO, JESSICA ANDREA; DUSSAUT, JULIETA SOL; PONZONI, IGNACIO; GALLO, CRISTIAN ANDRÉS

Buenos Aires

Congreso; ISCB Latin America 2016; 2016

International Society for Computational Biology (ISCB) y Asociación Argentina de Bioinformática y Biología Computacional (A2B2C)

Gene expression biclustering analysis is one of the most commonly used technique to see the interaction between genes under certain experiments or conditions. More specifically in diseases such as Alzheimer Disease (AD), this method is used to compare control and affected data in order to identify the involved genes. In some cases, discretization is needed for these algorithms to work correctly. Choosing the method of discretization for the data becomes extremely important, and has a major impact on the outcome. In this work we analyze several discretization methods for the AD gene expression data and compare the results of a biclustering algorithm on each different discretization.