Promoter Region Finder Calculator

Find likely promoter regions using motif scans, CpG tests, and statistics. Inspect candidate sites fast. Generate clear reports for exploratory genomic sequence screening workflows.

Enter sequence data

Use a short label for exported files and reports.
Choose the sequence class that best matches your organism.
Adds a starting coordinate when your sequence is part of a larger contig.
Higher values return fewer, stronger candidates.
Controls the number of ranked regions shown in the report.
Useful when scanning vertebrate promoter regions with CpG enrichment.
Applied only to the CpG island screen.
A classic CpG island filter often starts near 0.60.
Helpful when strand orientation is uncertain.
Only A, C, G, T, and N are used. Spaces and line breaks are removed automatically.

Example data table

Sequence name Model Length Top region Estimated TSS Top motifs Score
Human promoter sample Eukaryotic RNA polymerase II 300 bp 61 - 281 231 TATA, CAAT, GC box, CpG island 86.40
Bacterial operon sample Bacterial σ70-like promoter 180 bp 21 - 82 71 -35 box, -10 box, spacer 17 bp 78.10
GC-rich exploratory region Eukaryotic RNA polymerase II 420 bp 108 - 328 294 Inr, GC boxes ×2, CpG island 73.55

Formula used

1) GC content
GC% = ((G + C) / sequence length) × 100

2) CpG observed to expected ratio
Obs/Exp CpG = (number of CpG dinucleotides × window length) / (count(C) × count(G))

3) Motif similarity
Similarity = matching consensus positions / motif length

4) Eukaryotic promoter score
Score = Inr contribution + TATA contribution + CAAT contribution + GC-box contribution + CpG bonus + GC-richness bonus

5) Bacterial promoter score
Score = -35 contribution + -10 contribution + spacer bonus + upstream AT-rich bonus

This finder uses a weighted heuristic model. It prioritizes biologically common sequence patterns, spacing, and compositional features instead of claiming experimental promoter validation.

How to use this calculator

  1. Paste a DNA sequence in the sequence field. Mixed case, spaces, and line breaks are accepted.
  2. Select the promoter model that matches your organism or sequence context.
  3. Set score threshold, CpG filters, and candidate limit to control result sensitivity.
  4. Enable reverse complement scanning when the strand is unknown.
  5. Click Find promoter regions to rank likely promoter intervals.
  6. Review the top candidate, motif table, and CpG island report together.
  7. Export the ranked result table with CSV or PDF buttons for documentation.

FAQs

1) What does this promoter region finder do?

It scans DNA for promoter-like patterns and ranks likely regulatory intervals. The tool combines motif matches, spacing rules, GC composition, and optional CpG island evidence in one report.

2) Is this a confirmed promoter prediction tool?

No. It is a heuristic screening calculator for exploratory analysis. Strong scores suggest useful follow-up targets, but experimental validation or dedicated genomics pipelines are still necessary.

3) Which motifs are checked in eukaryotic mode?

The eukaryotic model checks TATA boxes, CAAT boxes, GC boxes, and initiator-like sequences. It also adds evidence from CpG-rich windows and broader GC content near candidate regions.

4) Which motifs are checked in bacterial mode?

The bacterial model looks for σ70-like promoter architecture, especially the -35 and -10 boxes. It also rewards near-optimal spacer length and an upstream AT-rich segment.

5) Why should I scan the reverse complement?

Genomic fragments are not always provided in the transcribed orientation. Reverse scanning helps catch promoter-like patterns on the opposite strand without manually reversing the sequence first.

6) What does the coordinate offset field do?

It shifts reported coordinates so exported results match your original genomic numbering. This is useful when you paste only a local fragment from a larger chromosome or contig.

7) How should I choose the score threshold?

Start around 45 to see broader candidates. Raise the threshold for stricter lists, or lower it when scanning weak or incomplete upstream fragments. Compare motifs instead of relying on one number.

8) What are the best next steps after scoring?

Compare top regions with known annotations, transcription start data, chromatin marks, or motif databases. The best candidate list is most useful as a shortlist for deeper biological review.

This page is intended for educational and exploratory bioinformatics use.

Related Calculators

hardy weinberg calculatoralignment score calculatorprimer design calculatororf finder toolexon intron ratiosequence length calculatorpcr cycle calculatorgenome assembly n50fragment size calculatorpairwise sequence identity

Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.