CONTRIBUTIONS TO THE STUDY OF BIG DATA ANALYTICS - C, Mithra
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This book explores the genetic adaptations of populations living in high altitude environments and the diseases they face. The researcher uses text mining and network analysis to identify the gene networks responsible for high altitude diseases. The author proposes a machine learning algorithm named Random Forest to predict miRNA-disease association using five modules: preprocessing, data analysis, feature extraction, dimensionality reduction, and prediction. The methodology is evaluated using precision, recall, F-measure, and accuracy. This research aims to improve the identification of…mehr

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Produktbeschreibung
This book explores the genetic adaptations of populations living in high altitude environments and the diseases they face. The researcher uses text mining and network analysis to identify the gene networks responsible for high altitude diseases. The author proposes a machine learning algorithm named Random Forest to predict miRNA-disease association using five modules: preprocessing, data analysis, feature extraction, dimensionality reduction, and prediction. The methodology is evaluated using precision, recall, F-measure, and accuracy. This research aims to improve the identification of disease genes from vast amounts of genetic data and provide a powerful tool for diagnosing, progressing, and treating human diseases.
Autorenporträt
Mithra C est professeur adjoint dans le département d'informatique et d'ingénierie à Vel Tech Rangarajan Dr. Sagunthala, l'Institut de R&D en sciences et technologies. Elle a obtenu son doctorat (CSE) à l'Université d'Annamalai et son M.E (CSE - Big Data) à l'Université d'Anna (campus CEG). Ses domaines d'intérêt comprennent l'exploration et l'analyse des données.