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Trends in microarray analysis

Nature Medicine, 2003
Microarrays permit the analysis of gene expression, DNA sequence variation, protein levels, tissues, cells and other biological and chemical molecules in a massively parallel format. Robust microarray manufacture, hybridization, detection and data analysis technologies permit novice users to adapt this exciting technology readily, and more experienced ...
Robin L, Stears   +2 more
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Microarray Analysis

2007
Microarrays and related technologies have allowed investigators to ask biological questions in far greater detail than has previously been possible. Microarrays had a troubled beginning, but most of these problems resulted from the growing pains of this technology, which, like many new things, was initially more promise than delivery.
Grier P, Page   +5 more
openaire   +2 more sources

Microarray Analysis of Hypertension

2017
Hypertension is a complex disorder in which multiple genes, pathways, and organ systems simultaneously interact to contribute to the final level of blood pressure. Fully elucidating these interactions is an important area of hypertension research and one in which high-throughput methods such as microarrays can play a key role.
Henry L, Keen, Curt D, Sigmund
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Microarray Data Analysis

2010
Gene expression profiling has revolutionized functional genomics research by providing a quick handle on all the transcriptional changes that occur in the cell in response to internal or external perturbations or developmental programs. Microarrays have become the most popular technology for recording gene expression profiles.
Saroj K, Mohapatra, Arjun, Krishnan
openaire   +2 more sources

MOLECULAR NETWORKS IN MICROARRAY ANALYSIS

Journal of Bioinformatics and Computational Biology, 2007
Microarray-based characterization of tissues, cellular and disease states, and environmental condition and treatment responses provides genome-wide snapshots containing large amounts of invaluable information. However, the lack of inherent structure within the data and strong noise make extracting and interpreting this information and formulating and ...
Andrey Y. Sivachenko   +3 more
openaire   +3 more sources

Microarray Analysis of Sarcomas

Advances in Anatomic Pathology, 2006
Microarrays began to be used to study gene expression profiles in the mid-1990s, but it was only after 2000 that serious attempts have been made to apply this technology to investigate sarcomas. Microarray technologies provide a comprehensive survey of active molecular pathways and potential molecular targets for diagnosis and treatment, but are ...
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Microarray Data Analysis Protocol

2021
Microarrays are broadly used in the omic investigation and have several areas of applications in biology and medicine, providing a significant amount of data for a single experiment. Different kinds of microarrays are available, identifiable by characteristics such as the type of probes, the surface used as support, and the method used for the target ...
Agapito G, Arbitrio M
openaire   +3 more sources

Methods for Microarray Data Analysis

2007
This chapter outlines a typical workflow for micraorray data analysis. It aims at explaining the background of the methods as this is necessary for deciding upon a specific numerical method to use and for understanding and interpreting the outcomes of the analyses.
De Bruyne, Veronique   +2 more
openaire   +3 more sources

Evolution of microarray analysis

Neurobiology of Aging, 2006
Reddy's very thorough review of the history of gene expression analysis of neurodegenerative disease made me think about the early days of microarrays, so I want to reminisce a little before commenting on the evolution of the technology and some issues that I think still continue to plague us.
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Microarray Data Analysis and Mining

2004
DNA microarray is an innovative technology for obtaining information on gene function. Because it is a high-throughput method, computational tools are essential in data analysis and mining to extract the knowledge from experimental results. Filtering procedures and statistical approaches are frequently combined to identify differentially expressed ...
SAVIOZZI, Silvia   +4 more
openaire   +5 more sources

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