A Profile HMM for Recognition of Hormone Response Elements

  • Maria Stepanova
  • Feng Lin
  • Valerie C. -L. Lin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4146)


Steroid hormones are necessary for most vital functions of vertebrate organisms, and act within cells via interaction with their receptor molecules. Steroid hormone receptors are transcription factors. Identification of Hormone response elements (HREs) on DNA is essential for understanding the mechanism of gene regulation by steroid hormones. In this work we present a systematic approach for recognition of steroid HREs within promoters of vertebrate genomes, based on extensive experimental dataset and specifically reconstructed Profile Hidden Markov Model of putative HREs. The model can be trained for further prediction of HREs in promoters of hormone responsive genes, and therefore, investigation of direct targets for androgen, progesterone and glucocorticoid hormones. Additional documentation and supplementary data, as well as the web-based program developed for steroid HRE prediction are available at .


Hide Markov Model Steroid Hormone Receptor Estrogen Response Element Hormone Response Element Primary Target Gene 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Maria Stepanova
    • 1
  • Feng Lin
    • 2
  • Valerie C. -L. Lin
    • 3
  1. 1.Bioinformatics Research CentreNanyang Technological UniversitySingapore
  2. 2.School of Computer EngineeringNanyang Technological UniversitySingapore
  3. 3.School of Biological SciencesNanyang Technological UniversitySingapore

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