Tag: Hierarchical Hidden Markov

HHMMiR 1.2 – Prediction of microRNAs using Hierarchical Hidden Markov models

HHMMiR 1.2

:: DESCRIPTION

HHMMiR is a novel approach for de novo miRNA hairpin prediction in the absence of evolutionary conservation. HHMMiR implements a Hierarchical Hidden Markov Model (HHMM) that utilizes region-based structural as well as sequence information of miRNA precursors.

:: DEVELOPER

Benos Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 HHMMiR

:: MORE INFORMATION

Citation:

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.