Bioinformatics resources for the study of gene regulation in bacteria - PubMed (original) (raw)

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Bioinformatics resources for the study of gene regulation in bacteria

Julio Collado-Vides et al. J Bacteriol. 2009 Jan.

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Figures

FIG. 1.

FIG. 1.

Number of published particles per organism. We searched through PubMed by using a collection of keywords that we regularly use to gather information for RegulonDB across different bacteria. The profile requires the name of the organism to be in the title.

FIG. 2.

FIG. 2.

Distribution of TFBSs. RegulonDB version 6.2 has 697 σ70 promoters, 421 of which have at least one characterized binding site for a TF. The figure displays the distribution of central positions of activator and repressor DNA-binding sites in the −95 to +20 interval. The percentage of promoters was divided by the number of activator or repressor DNA-binding sites with the center position within each interval of 10 bp. This figure can be compared to Fig. 2 in reference .

FIG. 3.

FIG. 3.

Intergenic distances of genes within and at transcription unit boundaries. The sharply different distributions of these distances enabled the use of a direct method to predict transcription units in the complete E. coli genome. This figure is very similar to Fig. 3 in reference .

FIG. 4.

FIG. 4.

Flowchart for gathering all regulation information for a single gene. Navigation options are shown, starting from the main page of RegulonDB with the name of a gene, melA or melR in this example. The MelR-CRP complex regulon is shown.

FIG. 5.

FIG. 5.

Flowchart for ChIP-chip data and genes with similar DNA-binding site motifs. The example uses as input a set of genes from a ChIP-chip experiment with LexA (109). RSAT (99, 105) was used to obtain the collection of upstream sequences, given the ChIP-chip gene set. The position-specific matrix (PSSM) for LexA was obtained by selecting Downloads → Data sets → Matrix alignment from the RegulonDB main menu. Then, it was pasted into RSAT to run a matrix scan. This program will search, given a threshold, for predicted sites in the complete set of upstream regions of the genome, and the results can be automatically obtained in a graphic display by using the feature map program.

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