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Showing 1 to 9 of 9 for “"gene expression data analysis"”.
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Clustering of Leukemia Patients via Gene Expression Data Analysis
… to cluster some leukemia patients described by gene expression data, and discover the most discriminating a few genes that are responsible for the clustering. A combined approach of Principal Direction Divisive Partitioning and bisect K-means algorithms is applied to the clustering of the …
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Microarray gene expression data analysis using machine learning and neural networks
… provides an effective way to measure the expression levels of tens of thousands of genes simultaneously under different conditions, which makes it possible to investigate the gene activities of the whole genome. However, computational challenges have to be faced as a result of the large …
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Microarray data analysis methods and their applications to gene expression data analysis for Saccharomyces cerevisiae under oxidative stress
… studies on Yap1 regulation started to measure gene expression profile at least 20 minutes after the induction of oxidative stress. Genes and pathways regulated by Yap1 in early oxidative stress response (within 20 minutes) were not identified in these studies. Here we study the kinetics of …
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A multi-level approach of gene expression data analysis to investigate translatome dynamics across multiple tissues, stages, and mouse models of SMA
… Atrophy (SMA) is an autosomal recessive neurodegenerative disease, which, before the approval of therapies, was the leading genetic cause of infant mortality. The primary features of this pathology are progressive muscle weakness and atrophy, due to the degeneration of α-motor neurons in the …
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Integrating Network Analysis and Data Mining Techniques into Effective Framework for Web Mining and Recommendation. A Framework for Web Mining and Recommendation
… in technology and the huge amount of available data which can be easily captured, stored and maintained electronically. We concentrate on Web usage (i.e., log) mining and Web structure mining. Analysing Web log data will reveal valuable feedback reflecting how effective the current structure of …
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Learning Statistical and Geometric Models from Microarray Gene Expression Data
… dissertation, we propose and develop innovative data modeling and analysis methods for extracting meaningful and specific information about disease mechanisms from microarray gene expression data. To provide a high-level overview of gene expression data for easy and insightful understanding of …
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Integrating statistical and mechanistic modeling to analyze disease omic data
Item withdrawn by Laura Spradlin (lspradl2@illinois.edu) on 2013-10-30T20:45:53Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 WANG_YULIANG.docx: 2952821 bytes, checksum: 08c2e350ebf29e4a14805992d55ba80f (MD5) WANG_YULIANG.pdf: 3382980 bytes, …
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Module-based Analysis of Biological Data for Network Inference and Biomarker Discovery
Systems biology comprises the global, integrated analysis of large-scale data encoding different levels of biological information with the aim to obtain global insight into the cellular networks. Several studies have unveiled the modular and hierarchical organization inherent in these networks. In …