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Quantification of global transcription patterns in prokaryotes using spotted microarrays

Ben Sidders1 email, Mike Withers1 email, Sharon L Kendall1 email, Joanna Bacon3 email, Simon J Waddell4 email, Jason Hinds4 email, Paul Golby5 email, Farahnaz Movahedzadeh1,6 email, Robert A Cox7 email, Rosangela Frita1 email, Annemieke MC ten Bokum8 email, Lorenz Wernisch2 email and Neil G Stoker1 email

1Department of Pathology and Infectious Diseases, Royal Veterinary College, Royal College Street, London, NW1 0TU, UK

2School of Crystallography, Birkbeck College, London, WC1E 7HX, UK

3TB Research, CEPR, Health Protection Agency, Porton Down, Salisbury, SP4 0JG, UK

4Medical Microbiology, Division of Cellular and Molecular Medicine, St George's University of London, Cranmer Terrace, Tooting, London, SW17 0RE, UK

5Veterinary Laboratories Agency, Woodham Lane, New Haw, Addlestone, Surrey, KT15 3NB, UK

6Institute for Tuberculosis Research College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, 60612-7231, USA

7Division of Mycobacterial Research, National Institute for Medical Research, The Ridgeway, Mill Hill, London, NW7 1AA, UK

8Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK

author email corresponding author email

Genome Biology 2007, 8:R265doi:10.1186/gb-2007-8-12-r265

Published: 13 December 2007

Subject areas: Bioinformatics, Genome studies, Microbiology and parasitology


Additional files

Additional data file 1:

The 198 genes of the 95th percentile; the very abundant transcripts in M. tuberculosis.

Format: XLS Size: 60KB Download file

This file can be viewed with: Microsoft Excel Viewer

Additional data file 2:

The quantified level of each functional category and details of those deemed significantly more or less abundant in the low oxygen transcriptome, including data from the three approaches to assess significance.

Format: XLS Size: 40KB Download file

This file can be viewed with: Microsoft Excel Viewer


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