Abstract-An active area of research in data mining and machine learning is dimensionality reduction. Feature subset selection is an effective technique for dimensionality reduction and an essential step in successful data mining applications. It reduces the number of features, removes irrelevant, redundant, or noisy features, and enhances the predictive capability of the classifier. It provides fast and cost-effective predictors and leading to better model comprehensibility. In this paper, we proposed a hybrid approach for feature subset selection. It is a filter based method in which a classifier ensemble is coupled with Ant colony optimization algorithm to enhance the predictive accuracy of filters. Extensive experimentation has been carried out on eleven data sets over four different classifiers. All of the data sets are available publically. We have compared our proposed method with numerous filter and wrapper based methods. Experimental results indicate that our method has remarkable ability to generate subsets with reduced number of features. Along with it, our proposed method attained higher classification accuracy.
Age-associated neurodegenerative diseases are known to have “impaired protein clearance” as one of the key features causing their onset and progression. Hence, homeostasis is the key to maintaining balance throughout the cellular system as an organism ages. Any imbalance in the protein clearance machinery is responsible for accumulation of unwanted proteins, leading to pathological consequences—manifesting in neurodegeneration and associated debilitating outcomes. Multiple processes are involved in regulating this phenomenon; however, failure to regulate the autophagic machinery is a critical process that hampers the protein clearing pathway, leading to neurodegeneration. Another important and widely known component that plays a role in modulating neurodegeneration is a class of proteins called sirtuins. These are class III histone deacetylases (HDACs) that are known to regulate various vital processes such as longevity, genomic stability, transcription and DNA repair. These enzymes are also known to modulate neurodegeneration in an autophagy-dependent manner. Considering its genetic relevance and ease of studying disease-related endpoints in neurodegeneration, the model system Caenorhabditis elegans has been successfully employed in deciphering various functional outcomes related to critical protein molecules, cell death pathways and their association with ageing. This review summarizes the vital role of sirtuins and autophagy in ageing and neurodegeneration, in particular highlighting the knowledge obtained using the C. elegans model system.
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