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TAMEE: data management and analysis for tissue microarrays

BACKGROUND: With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are req...

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Autores principales: Thallinger, Gerhard G, Baumgartner, Kerstin, Pirklbauer, Martin, Uray, Martina, Pauritsch, Elke, Mehes, Gabor, Buck, Charles R, Zatloukal, Kurt, Trajanoski, Zlatko
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1838435/
https://www.ncbi.nlm.nih.gov/pubmed/17343750
http://dx.doi.org/10.1186/1471-2105-8-81
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author Thallinger, Gerhard G
Baumgartner, Kerstin
Pirklbauer, Martin
Uray, Martina
Pauritsch, Elke
Mehes, Gabor
Buck, Charles R
Zatloukal, Kurt
Trajanoski, Zlatko
author_facet Thallinger, Gerhard G
Baumgartner, Kerstin
Pirklbauer, Martin
Uray, Martina
Pauritsch, Elke
Mehes, Gabor
Buck, Charles R
Zatloukal, Kurt
Trajanoski, Zlatko
author_sort Thallinger, Gerhard G
collection PubMed
description BACKGROUND: With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories. RESULTS: TAMEE (Tissue Array Management and Evaluation Environment) is a web-based database application for the management and analysis of data resulting from the production and application of TMAs. It facilitates storage of production and experimental parameters, of images generated throughout the TMA workflow, and of results from core evaluation. Database content consistency is achieved using structured classifications of parameters. This allows the extraction of high quality results for subsequent biologically-relevant data analyses. Tissue cores in the images of stained tissue sections are automatically located and extracted and can be evaluated using a set of predefined analysis algorithms. Additional evaluation algorithms can be easily integrated into the application via a plug-in interface. Downstream analysis of results is facilitated via a flexible query generator. CONCLUSION: We have developed an integrated system tailored to the specific needs of research projects using high density TMAs. It covers the complete workflow of TMA production, experimental use and subsequent analysis. The system is freely available for academic and non-profit institutions from .
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spelling pubmed-18384352007-03-28 TAMEE: data management and analysis for tissue microarrays Thallinger, Gerhard G Baumgartner, Kerstin Pirklbauer, Martin Uray, Martina Pauritsch, Elke Mehes, Gabor Buck, Charles R Zatloukal, Kurt Trajanoski, Zlatko BMC Bioinformatics Software BACKGROUND: With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories. RESULTS: TAMEE (Tissue Array Management and Evaluation Environment) is a web-based database application for the management and analysis of data resulting from the production and application of TMAs. It facilitates storage of production and experimental parameters, of images generated throughout the TMA workflow, and of results from core evaluation. Database content consistency is achieved using structured classifications of parameters. This allows the extraction of high quality results for subsequent biologically-relevant data analyses. Tissue cores in the images of stained tissue sections are automatically located and extracted and can be evaluated using a set of predefined analysis algorithms. Additional evaluation algorithms can be easily integrated into the application via a plug-in interface. Downstream analysis of results is facilitated via a flexible query generator. CONCLUSION: We have developed an integrated system tailored to the specific needs of research projects using high density TMAs. It covers the complete workflow of TMA production, experimental use and subsequent analysis. The system is freely available for academic and non-profit institutions from . BioMed Central 2007-03-07 /pmc/articles/PMC1838435/ /pubmed/17343750 http://dx.doi.org/10.1186/1471-2105-8-81 Text en Copyright © 2007 Thallinger et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Thallinger, Gerhard G
Baumgartner, Kerstin
Pirklbauer, Martin
Uray, Martina
Pauritsch, Elke
Mehes, Gabor
Buck, Charles R
Zatloukal, Kurt
Trajanoski, Zlatko
TAMEE: data management and analysis for tissue microarrays
title TAMEE: data management and analysis for tissue microarrays
title_full TAMEE: data management and analysis for tissue microarrays
title_fullStr TAMEE: data management and analysis for tissue microarrays
title_full_unstemmed TAMEE: data management and analysis for tissue microarrays
title_short TAMEE: data management and analysis for tissue microarrays
title_sort tamee: data management and analysis for tissue microarrays
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1838435/
https://www.ncbi.nlm.nih.gov/pubmed/17343750
http://dx.doi.org/10.1186/1471-2105-8-81
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