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softberry bprom algorithm  (Softberry Inc)

 
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    Softberry Inc softberry bprom algorithm
    Identification of tpxD regulatory promoter elements. (A) In silico analysis of tpxD proximal promoter region. Identification of tpxD promoter elements using <t>BPROM</t> <t>algorithm:</t> ATG start codon (1); Shine Dalgarno (2); transcription start site at A (3); −10 and −35 elements of the σ 70 promoter (4 and 5, respectively). The first nucleotide included in each of the Δ tpxD comp mutants (1–6) is indicated by arrow. (B) Influence of tpxD putative regulatory elements on TpxD expression levels under H 2 O 2 stress. TpxD levels, determined by Western blotting, were measured in D39, Δ tpxD and Δ tpxD comp1-6 (described in Figure ). Bacteria were grown anaerobically to OD 620 = 0.25 and then challenged with 1 mM H 2 O 2 for 40 min. Separated proteins were electroblotted onto 0.45 μm nitrocellulose membrane, and stained with Ponceau S to ensure equal loading, before incubation with antibodies. Membranes were exposed for long time intervals to ensure the absence of bands in Δ tpxD comp1-4 and are lined up, as indicated in the figure. Densitometry was performed using ImageJ software.
    Softberry Bprom Algorithm, supplied by Softberry Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/softberry+bprom+algorithm/bprom+algorithm/pmc05443158-112-7-6
    Average 90 stars, based on 1 article reviews
    softberry bprom algorithm - by Bioz Stars, 2026-09
    90/100 stars

    Images

    1) Product Images from "CodY Regulates Thiol Peroxidase Expression as Part of the Pneumococcal Defense Mechanism against H 2 O 2 Stress"

    Article Title: CodY Regulates Thiol Peroxidase Expression as Part of the Pneumococcal Defense Mechanism against H 2 O 2 Stress

    Journal: Frontiers in Cellular and Infection Microbiology

    doi: 10.3389/fcimb.2017.00210

    Identification of tpxD regulatory promoter elements. (A) In silico analysis of tpxD proximal promoter region. Identification of tpxD promoter elements using BPROM algorithm: ATG start codon (1); Shine Dalgarno (2); transcription start site at A (3); −10 and −35 elements of the σ 70 promoter (4 and 5, respectively). The first nucleotide included in each of the Δ tpxD comp mutants (1–6) is indicated by arrow. (B) Influence of tpxD putative regulatory elements on TpxD expression levels under H 2 O 2 stress. TpxD levels, determined by Western blotting, were measured in D39, Δ tpxD and Δ tpxD comp1-6 (described in Figure ). Bacteria were grown anaerobically to OD 620 = 0.25 and then challenged with 1 mM H 2 O 2 for 40 min. Separated proteins were electroblotted onto 0.45 μm nitrocellulose membrane, and stained with Ponceau S to ensure equal loading, before incubation with antibodies. Membranes were exposed for long time intervals to ensure the absence of bands in Δ tpxD comp1-4 and are lined up, as indicated in the figure. Densitometry was performed using ImageJ software.
    Figure Legend Snippet: Identification of tpxD regulatory promoter elements. (A) In silico analysis of tpxD proximal promoter region. Identification of tpxD promoter elements using BPROM algorithm: ATG start codon (1); Shine Dalgarno (2); transcription start site at A (3); −10 and −35 elements of the σ 70 promoter (4 and 5, respectively). The first nucleotide included in each of the Δ tpxD comp mutants (1–6) is indicated by arrow. (B) Influence of tpxD putative regulatory elements on TpxD expression levels under H 2 O 2 stress. TpxD levels, determined by Western blotting, were measured in D39, Δ tpxD and Δ tpxD comp1-6 (described in Figure ). Bacteria were grown anaerobically to OD 620 = 0.25 and then challenged with 1 mM H 2 O 2 for 40 min. Separated proteins were electroblotted onto 0.45 μm nitrocellulose membrane, and stained with Ponceau S to ensure equal loading, before incubation with antibodies. Membranes were exposed for long time intervals to ensure the absence of bands in Δ tpxD comp1-4 and are lined up, as indicated in the figure. Densitometry was performed using ImageJ software.

    Techniques Used: In Silico, Expressing, Western Blot, Staining, Incubation, Software

    Related Articles

    Introduce:

    Article Title: Cell Aggregation and Aerobic Respiration Are Important for Zymomonas mobilis ZM4 Survival in an Aerobic Minimal Medium
    Article Snippet: .. Primers were designed to amplify entire genes and promoter regions as predicted using the BPROM algorithm (Softberry, Inc.) ( 45 ) and to introduce flanking ScaI and KpnI restriction sites. ..

    Sequencing:

    Article Title: Evolutionary Trajectories of Methionine Metabolism in Mycobacterium and Its Application to Engineer a Vitamin B12 Whole‐Cell Ribosensor
    Article Snippet: .. The putative −10 mycobacterial sequence was predicted only using the BPROM algorithm ( http://www.softberry.com/berry.phtml?topic=bprom ) (Solovyev ). ..

    other:

    Article Title: Binding site profiles and N-terminal minor groove interactions of the master quorum-sensing regulator LuxR enable flexible control of gene activation and repression
    Article Snippet: The transcriptional start sites (TSS) was predicted by the Softberry-BPROM algorithm ( http://www.softberry.com ) and manually checked with the strand-specific RNA-seq determined TSS.

    Article Title: Protein-only RNase P function in Escherichia coli : viability, processing defects and differences between PRORP isoenzymes
    Article Snippet: A search for putative promoters upstream of the 4.5S RNA gene ( http://regulondb.ccg.unam.mx ; Softberry, BPROM algorithm; http://www.softberry.com ) gave predictions for transcription start points of σ 70 RNA polymerase at positions –160, –130 and –26 relative to the mature 5 ́-end (nt +1) of 4.5S RNA.



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    Identification of tpxD regulatory promoter elements. (A) In silico analysis of tpxD proximal promoter region. Identification of tpxD promoter elements using <t>BPROM</t> <t>algorithm:</t> ATG start codon (1); Shine Dalgarno (2); transcription start site at A (3); −10 and −35 elements of the σ 70 promoter (4 and 5, respectively). The first nucleotide included in each of the Δ tpxD comp mutants (1–6) is indicated by arrow. (B) Influence of tpxD putative regulatory elements on TpxD expression levels under H 2 O 2 stress. TpxD levels, determined by Western blotting, were measured in D39, Δ tpxD and Δ tpxD comp1-6 (described in Figure ). Bacteria were grown anaerobically to OD 620 = 0.25 and then challenged with 1 mM H 2 O 2 for 40 min. Separated proteins were electroblotted onto 0.45 μm nitrocellulose membrane, and stained with Ponceau S to ensure equal loading, before incubation with antibodies. Membranes were exposed for long time intervals to ensure the absence of bands in Δ tpxD comp1-4 and are lined up, as indicated in the figure. Densitometry was performed using ImageJ software.
    Softberry Bprom Algorithm, supplied by Softberry Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/softberry+bprom+algorithm/bprom+algorithm/pmc05443158-112-7-6
    Average 90 stars, based on 1 article reviews
    softberry bprom algorithm - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Identification of tpxD regulatory promoter elements. (A) In silico analysis of tpxD proximal promoter region. Identification of tpxD promoter elements using BPROM algorithm: ATG start codon (1); Shine Dalgarno (2); transcription start site at A (3); −10 and −35 elements of the σ 70 promoter (4 and 5, respectively). The first nucleotide included in each of the Δ tpxD comp mutants (1–6) is indicated by arrow. (B) Influence of tpxD putative regulatory elements on TpxD expression levels under H 2 O 2 stress. TpxD levels, determined by Western blotting, were measured in D39, Δ tpxD and Δ tpxD comp1-6 (described in Figure ). Bacteria were grown anaerobically to OD 620 = 0.25 and then challenged with 1 mM H 2 O 2 for 40 min. Separated proteins were electroblotted onto 0.45 μm nitrocellulose membrane, and stained with Ponceau S to ensure equal loading, before incubation with antibodies. Membranes were exposed for long time intervals to ensure the absence of bands in Δ tpxD comp1-4 and are lined up, as indicated in the figure. Densitometry was performed using ImageJ software.

    Journal: Frontiers in Cellular and Infection Microbiology

    Article Title: CodY Regulates Thiol Peroxidase Expression as Part of the Pneumococcal Defense Mechanism against H 2 O 2 Stress

    doi: 10.3389/fcimb.2017.00210

    Figure Lengend Snippet: Identification of tpxD regulatory promoter elements. (A) In silico analysis of tpxD proximal promoter region. Identification of tpxD promoter elements using BPROM algorithm: ATG start codon (1); Shine Dalgarno (2); transcription start site at A (3); −10 and −35 elements of the σ 70 promoter (4 and 5, respectively). The first nucleotide included in each of the Δ tpxD comp mutants (1–6) is indicated by arrow. (B) Influence of tpxD putative regulatory elements on TpxD expression levels under H 2 O 2 stress. TpxD levels, determined by Western blotting, were measured in D39, Δ tpxD and Δ tpxD comp1-6 (described in Figure ). Bacteria were grown anaerobically to OD 620 = 0.25 and then challenged with 1 mM H 2 O 2 for 40 min. Separated proteins were electroblotted onto 0.45 μm nitrocellulose membrane, and stained with Ponceau S to ensure equal loading, before incubation with antibodies. Membranes were exposed for long time intervals to ensure the absence of bands in Δ tpxD comp1-4 and are lined up, as indicated in the figure. Densitometry was performed using ImageJ software.

    Article Snippet: Promoter elements were predicted using the Softberry BPROM algorithm of bacterial promoters ( http://www.softberry.com/berry.phtml?topic=bprom&group=programs&subgroup=gfindb ).

    Techniques: In Silico, Expressing, Western Blot, Staining, Incubation, Software