Navigating the world of bacterial promoters can be complex, but with the right tools, you can unlock remarkable potential in your genetic design projects. This guide addresses a key question: does your DNA sequence contain promoter-like motifs commonly found in bacterial regulatory regions?

XGBoost Promoter Evaluation

The model presented below is an XGBoost-based classifier adapted from code originally developed by Jannis and trained on the samira1992/promoter-or-not bioinformatics dataset. It evaluates DNA sequences for promoter-like characteristics using predefined features, including GC content, CpG ratio, di-Shannon entropy, AT and GC skew, −35 and −10 boxes, internal motifs, and a weighted TATA sequence score.

This approach is fast, lightweight, and deterministic, providing stable and interpretable predictions that clearly show which features influenced the classification. However, it is limited to the features it was trained on, may miss non-canonical or unusual promoters, and can reach a performance ceiling on complex sequences.