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 Online Journal of Bioinformatics  

Volume 10(1):51-59, 2009.

 A systematic approach to understanding Escherichia coli responses to oxygen:

 From microarray raw data to pathways and published abstracts


Maleki-Dizaji S1,*, Holcombe M1, Rolfe MD2, Fisher P3,  Green J2,  Poole RK2,  Graham AI2, SYSMO-SUMO consortium4


1Department of Computer Science, The University of Sheffield, Sheffield S1 4DP, United Kingdom. 2Department of Molecular Biology and Biotechnology, The University of Sheffield, Sheffield S10 2TN, United Kingdom. 3Department of Computer Science, The University of Manchester, Manchester M13 9PL, United Kingdom. 4See acknowledgements.




Maleki-Dizaji S, Holcombe M, Rolfe MD, Fisher P, Green J, Poole RK, Graham AI,  A Systematic Approach to Understanding Escherichia coli Responses to Oxygen: From Microarray Raw Data to Pathways and Published Abstracts, Online J Bioinformatics, 10(1):51-59, 2009.  Genome-wide transcript-profiling has transformed the study of gene regulation in bacteria and other organisms. However, analyses of these microarray datasets to identify regulons, pathways and relevant literature are often user-intensive. Here, a transcript-profiling study comparing Escherichia coli cultures from aerobic and anaerobic conditions is used to develop a data-driven methodology that identifies the known metabolic pathways and regulons present in a set of differentially expressed genes. These are subsequently used to obtain a corpus of published abstracts (from the PubMed database) relating to each biological pathway. Thus, the workflow facilitates consistent and user-friendly interrogation of transcriptomic datasets allowing experimentalists to focus on advanced data analysis and interpretational tasks.


Keywords: E. coli, Microarray, Taverna Workflow, Web Services.