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accession-icon GSE2430
Azithromycin-treated PAO1 vs untreated PAO1
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

Experimental Design

Publication Title

Quorum-sensing antagonistic activities of azithromycin in Pseudomonas aeruginosa PAO1: a global approach.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE33160
Regulatory network underlying the adaptive physiology of Pseudomonas aeruginosa under urinary tract-like conditions
  • organism-icon Pseudomonas aeruginosa pao1
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

Pseudomonas aeruginosa is one of the most frequent pathogen dominant in complicated urinary tract infections (UTI). To unravel the adaptation strategies of P. aeruginosa to the conditions in the urinary tract and to define the underlying regulatory network an artificial growth system mimicking the conditions in the urinary tract was established. Transcriptome analyses were used to investigate the physiological status of P. aeruginosa under this conditions.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE17179
Definition of the Pseudomonas aeruginosa Anr and Dnr Regulons
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

The anaerobic metabolism of the opportunistic pathogen Pseudomonas aeruginosa is important for growth and survival during persistent infections. The two Fnr-type transcription factors Anr and Dnr regulate different parts of the underlying network. Both are proposed to bind to a non-distinguishable DNA sequence named Anr box.

Publication Title

Anaerobic adaptation in Pseudomonas aeruginosa: definition of the Anr and Dnr regulons.

Sample Metadata Fields

No sample metadata fields

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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