Results 161 to 170 of about 557,537 (198)
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2005
During the last 10 years and in particularly within the last few years, there has been a data explosion associated with the completion of the human genome project (HGP) (IHGMC and Venter et al., 2001) in 2001 and the many sophisticated genomics technologies.
Nanxiang Ge, Li Liu
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During the last 10 years and in particularly within the last few years, there has been a data explosion associated with the completion of the human genome project (HGP) (IHGMC and Venter et al., 2001) in 2001 and the many sophisticated genomics technologies.
Nanxiang Ge, Li Liu
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Analysis of DNA Microarray Data
Current Topics in Medicinal Chemistry, 2004Recent advances in DNA microarray technology have great impact on many areas of biomedical research and pharmacogenomics: discovering novel targets and genes, elucidating signatures of complex diseases, transcriptional profiling of models for diseases, and the development of individually optimized drugs based on differential gene expression patterns ...
Hubert, Hackl +4 more
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2005
In this chapter, we discuss several analytical techniques and tools used in image analysis of microarray for data extraction and data analysis for pattern discovery such as cluster analysis, temporal expression profile analysis, and gene regulation analysis.
Liew, AWC, Yan, H, Yang, M, Chen, YPP
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In this chapter, we discuss several analytical techniques and tools used in image analysis of microarray for data extraction and data analysis for pattern discovery such as cluster analysis, temporal expression profile analysis, and gene regulation analysis.
Liew, AWC, Yan, H, Yang, M, Chen, YPP
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Extracting meaning from microarray data
Biochemical Society Transactions, 2003Gene expression is complex: many mRNAs change in abundance in response to a new condition. But while some of these expression changes may be direct, many may be downstream, indirect effects. One of the major problems of microarray data analysis is distinguishing between these changes.
R K, Curtis, M D, Brand
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Building Networks with Microarray Data
2009This chapter describes methods for learning gene interaction networks from high-throughput gene expression data sets. Many genes have unknown or poorly understood functions and interactions, especially in diseases such as cancer where the genome is frequently mutated. The gene interactions inferred by learning a network model from the data can form the
Bradley M, Broom +3 more
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Integrating Microarray Data and GRNs
2015With the completion of the Human Genome Project and the emergence of high-throughput technologies, a vast amount of molecular and biological data are being produced. Two of the most important and significant data sources come from microarray gene-expression experiments and respective databanks (e,g., Gene Expression Omnibus-GEO (http://www.ncbi.nlm.nih.
L, Koumakis +4 more
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2005
Based on the concept of simultaneously studying the expression of a large number of genes, a DNA microarray is a chip on which numerous probes are placed for hybridization with a tissue sample. Biological complexity encoded by a deluge of microarray data is being translated into all sorts of computational, statistical, or mathematical problems bearing ...
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Based on the concept of simultaneously studying the expression of a large number of genes, a DNA microarray is a chip on which numerous probes are placed for hybridization with a tissue sample. Biological complexity encoded by a deluge of microarray data is being translated into all sorts of computational, statistical, or mathematical problems bearing ...
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Methods for Processing Microarray Data
Cold Spring Harbor Protocols, 2014Quality control must be maintained at every step of a microarray experiment, from RNA isolation through statistical evaluation. Here we provide suggestions for analyzing microarray data. Because the utility of the results depends directly on the design of the experiment, the first critical step is to ensure that the experiment can be properly analyzed ...
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Microarray technology has revolutionized the field of genomics by enabling quantitative measurement of gene expression levels for thousands of genes in a single experiment. This high-throughput technique has been instrumental in the understanding of biological processes, identification of biomarkers for diseases, and exploring molecular pathways of ...
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Methods in enzymology, 2006
Even a simple, small-scale, microarray experiment generates thousands to millions of data points. Clearly, spreadsheets or plotting programs do not suffice for analysis of such large volumes of data, and comprehensive analysis requires systematic methods for selection and organization of data.
Jeremy, Gollub, Gavin, Sherlock
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Even a simple, small-scale, microarray experiment generates thousands to millions of data points. Clearly, spreadsheets or plotting programs do not suffice for analysis of such large volumes of data, and comprehensive analysis requires systematic methods for selection and organization of data.
Jeremy, Gollub, Gavin, Sherlock
openaire +1 more source