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softberry-bprom algorithm  (Softberry Inc)

 
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    Softberry Inc softberry-bprom algorithm
    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/bprom+algorithm/bprom+algorithm/pmc08034623-128-9-12
    Average 90 stars, based on 1 article reviews
    softberry-bprom algorithm - by Bioz Stars, 2026-09
    90/100 stars

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    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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    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.
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    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