Kadri et al. (2009) BMC BIoinformatics (Proc APBC 2009)

Supplementary Material and Data Downloads

 

S. Kadri, V. Hinman, P.V. Benos, "HHMMiR: Efficient de novo Prediction of MicroRNAs using Hierarchical Hidden Markov Models",     BMC Bioinformatics (Proc APBC 2009) (2009) 10 (Suppl 1):S35.

  The supplementary material included here is summary characteristics of regions of miRNA stemloops for various species, detailed description of the HHMM model, and the training and testing datasets used in this study.

• miRNA cross-species characteristics
  Summary characteristics of regions of miRNA stemloops for various species.
  
• HHMMiR algorithm
  More detailed description of the HHMM model.
  
• Supplementary Data
  Training and testing datasets used in this study.
  
• HHMMiR models
  HHMMiR models trained on human miRNA sequences. These models were used for the predictions in the paper.