Microarray Gene Subset Selection in Amyotrophic Lateral Sclerosis Classification

作者: Edgar A. Castro-Astengo , Felix F. Gonz´lez-Navarro , Brenda A. Flores-Rios

DOI: 10.1109/MICAI.2011.15

关键词: BioinformaticsFeature selectionBiologyAmyotrophic lateral sclerosisDiseaseGeneMicroarrayGene mutationStability (learning theory)Selection (genetic algorithm)

摘要: Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease causing progressive loss of motor neurons. The prevalence 5 per 100,000 people. There no cure and it leads generally to death from respiratory failure in approximately 3-5 years after the first symptoms. exact causes are still unknown, however, almost 20% known cases have shown gene mutations. use expression analysis powerful tool discover most relevant genes cellular process, but high dimensionality data makes feature selection challenging task. Using filter method combined with machine learning algorithms, an ALS set explored. Bootstrap resampling used as way achieve stability whole process.

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