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Microarrays, Volume 1, Issue 2 (September 2012), Pages 64-106

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Research

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Open AccessArticle Quality Visualization of Microarray Datasets Using Circos
Microarrays 2012, 1(2), 84-94; doi:10.3390/microarrays1020084
Received: 25 June 2012 / Revised: 25 July 2012 / Accepted: 3 August 2012 / Published: 7 August 2012
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Abstract
Quality control and normalization is considered the most important step in the analysis of microarray data. At present there are various methods available for quality assessments of microarray datasets. However there seems to be no standard visualization routine, which also depicts individual [...] Read more.
Quality control and normalization is considered the most important step in the analysis of microarray data. At present there are various methods available for quality assessments of microarray datasets. However there seems to be no standard visualization routine, which also depicts individual microarray quality. Here we present a convenient method for visualizing the results of standard quality control tests using Circos plots. In these plots various quality measurements are drawn in a circular fashion, thus allowing for visualization of the quality and all outliers of each distinct array within a microarray dataset. The proposed method is intended for use with the Affymetrix Human Genome platform (i.e., GPL 96, GPL570 and GPL571). Circos quality measurement plots are a convenient way for the initial quality estimate of Affymetrix datasets that are stored in publicly available databases. Full article
(This article belongs to the Special Issue Feature Papers)
Open AccessArticle Development and Optimization of a Thrombin Sandwich Aptamer Microarray
Microarrays 2012, 1(2), 95-106; doi:10.3390/microarrays1020095
Received: 28 June 2012 / Revised: 26 July 2012 / Accepted: 7 August 2012 / Published: 8 August 2012
Cited by 4 | PDF Full-text (687 KB) | HTML Full-text | XML Full-text
Abstract
A sandwich microarray employing two distinct aptamers for human thrombin has been optimized for the detection of subnanomolar concentrations of the protein. The aptamer microarray demonstrates high specificity for thrombin, proving that a two-site binding assay with the TBA1 aptamer as capture [...] Read more.
A sandwich microarray employing two distinct aptamers for human thrombin has been optimized for the detection of subnanomolar concentrations of the protein. The aptamer microarray demonstrates high specificity for thrombin, proving that a two-site binding assay with the TBA1 aptamer as capture layer and the TBA2 aptamer as detection layer can ensure great specificity at times and conditions compatible with standard routine analysis of biological samples. Aptamer microarray sensitivity was evaluated directly by fluorescent analysis employing Cy5-labeled TBA2 and indirectly by the use of TBA2-biotin followed by detection with fluorescent streptavidin. Sub-nanomolar LODs were reached in all cases and in the presence of serum, demonstrating that the optimized aptamer microarray can identify thrombin by a low-cost, sensitive and specific method. Full article
(This article belongs to the Special Issue Feature Papers)
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Review

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Open AccessReview Data Analysis Strategies for Protein Microarrays
Microarrays 2012, 1(2), 64-83; doi:10.3390/microarrays1020064
Received: 13 June 2012 / Revised: 13 July 2012 / Accepted: 31 July 2012 / Published: 6 August 2012
Cited by 4 | PDF Full-text (618 KB) | HTML Full-text | XML Full-text
Abstract
Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and [...] Read more.
Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and the characterization of protein expression patterns. However, the analysis and interpretation of the amount of information generated by microarrays remain a challenge. Further data analysis strategies are essential to obtain representative and reproducible results. Therefore, the experimental design is key, since the number of samples and dyes, among others aspects, would define the appropriate analysis method to be used. In this sense, several algorithms have been proposed so far to overcome analytical difficulties derived from fluorescence overlapping and/or background noise. Each kind of microarray is developed to fulfill a specific purpose. Therefore, the selection of appropriate analytical and data analysis strategies is crucial to achieve successful biological conclusions. In the present review, we focus on current algorithms and main strategies for data interpretation. Full article
(This article belongs to the Special Issue Feature Papers)
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