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CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data. / Feichtinger, Julia; Mcfarlane, Ramsay; Larcombe, Lee.

Yn: Database: The Journal of Biological Databases and Curation, Cyfrol 2012, bas055, 15.12.2012.

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygl

HarvardHarvard

Feichtinger, J, Mcfarlane, R & Larcombe, L 2012, 'CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data.', Database: The Journal of Biological Databases and Curation, cyfrol. 2012, bas055. https://doi.org/10.1093/database/bas055

APA

Feichtinger, J., Mcfarlane, R., & Larcombe, L. (2012). CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data. Database: The Journal of Biological Databases and Curation, 2012, [bas055]. https://doi.org/10.1093/database/bas055

CBE

Feichtinger J, Mcfarlane R, Larcombe L. 2012. CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data. Database: The Journal of Biological Databases and Curation. 2012. https://doi.org/10.1093/database/bas055

MLA

Feichtinger, Julia, Ramsay Mcfarlane a Lee Larcombe. "CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data.". Database: The Journal of Biological Databases and Curation. 2012. 2012. https://doi.org/10.1093/database/bas055

VancouverVancouver

Feichtinger J, Mcfarlane R, Larcombe L. CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data. Database: The Journal of Biological Databases and Curation. 2012 Dec 15;2012. bas055. https://doi.org/10.1093/database/bas055

Author

Feichtinger, Julia ; Mcfarlane, Ramsay ; Larcombe, Lee. / CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data. Yn: Database: The Journal of Biological Databases and Curation. 2012 ; Cyfrol 2012.

RIS

TY - JOUR

T1 - CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data.

AU - Feichtinger, Julia

AU - Mcfarlane, Ramsay

AU - Larcombe, Lee

PY - 2012/12/15

Y1 - 2012/12/15

N2 - The identification of novel candidate markers is a key challenge in the development of cancer therapies. This can be facilitated by putting accessible and automated approaches analysing the current wealth of 'omic'-scale data in the hands of researchers who are directly addressing biological questions. Data integration techniques and standardized, automated, high-throughput analyses are needed to manage the data available as well as to help narrow down the excessive number of target gene possibilities presented by modern databases and system-level resources. Here we present CancerMA, an online, integrated bioinformatic pipeline for automated identification of novel candidate cancer markers/targets; it operates by means of meta-analysing expression profiles of user-defined sets of biologically significant and related genes across a manually curated database of 80 publicly available cancer microarray datasets covering 13 cancer types. A simple-to-use web interface allows bioinformaticians and non-bioinformaticians alike to initiate new analyses as well as to view and retrieve the meta-analysis results. The functionality of CancerMA is shown by means of two validation datasets.

AB - The identification of novel candidate markers is a key challenge in the development of cancer therapies. This can be facilitated by putting accessible and automated approaches analysing the current wealth of 'omic'-scale data in the hands of researchers who are directly addressing biological questions. Data integration techniques and standardized, automated, high-throughput analyses are needed to manage the data available as well as to help narrow down the excessive number of target gene possibilities presented by modern databases and system-level resources. Here we present CancerMA, an online, integrated bioinformatic pipeline for automated identification of novel candidate cancer markers/targets; it operates by means of meta-analysing expression profiles of user-defined sets of biologically significant and related genes across a manually curated database of 80 publicly available cancer microarray datasets covering 13 cancer types. A simple-to-use web interface allows bioinformaticians and non-bioinformaticians alike to initiate new analyses as well as to view and retrieve the meta-analysis results. The functionality of CancerMA is shown by means of two validation datasets.

U2 - 10.1093/database/bas055

DO - 10.1093/database/bas055

M3 - Article

VL - 2012

JO - Database: The Journal of Biological Databases and Curation

JF - Database: The Journal of Biological Databases and Curation

SN - 1758-0463

M1 - bas055

ER -