Plant promoter prediction with confidence estimation

I. A. Shahmuradov, Victor V. Solovyev*, A. J. Gammerman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

111 Scopus citations


Accurate prediction of promoters is fundamental to understanding gene expression patterns, where confidence estimation is one of the main requirements. Using recently developed transductive confidence machine (TCM) techniques, we developed a new program TSSP-TCM for the prediction of plant promoters that also provides confidence of the prediction. The program was trained on 132 and 104 sequences and tested on 40 and 25 sequences (containing TATA and TATA-less promoters, respectively) with known transcription start sites (TSSs). As negative training samples for TCM learning we used coding and intron sequences of plant genes annotated in the GenBank. In the test set of TATA promoters, the program correctly predicted TSS for 35 out of 40 (87.5%) genes with a median deviation of several base pairs from the true site location. For 25 TATA-less promoters, TSSs were predicted for 21 out of 25 (84%) genes, including 14 cases of 5 bp distance between annotated and predicted TSSs. Using TSSP-TCM program we annotated promoters in the whole Arabidopsis genome. The predicted promoters were in good agreement with the start position of known Arabidopsis mRNAs. Thus, TCM technique has produced a plant-oriented promoter prediction tool of high accuracy. TSSP-TCM program and annotated promoters are available at

Original languageEnglish (US)
Pages (from-to)1069-1076
Number of pages8
Issue number3
StatePublished - 2005
Externally publishedYes

Bibliographical note

Funding Information:
PlantProm Database is designed and maintained at Royal Holloway, University of London in collaboration with Softberry Inc. (USA). This work was partially supported by BBSRC grant 111/BIO14428 ‘Pattern recognition techniques for gene and promoter identification and classification in plant genomic sequences’. Funding to pay the Open Access publication charges for this article was provided by JICS, UK.

ASJC Scopus subject areas

  • Genetics


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