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A computational tool utilizing a probabilistic method based on Profile Hidden Markov Models to predict novel miRNA precursors. Via the simultaneous integration of biological features such as sequence, structure and conservation, SSCprofiler achieves a performance accuracy of 88.95% sensitivity and 84.16% specificity on a large set of human miRNA genes.

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SSCprofiler classification

SSCprofiler specifications

Unique identifier:
OMICS_02055
Interface:
Web user interface
Computer skills:
Basic
Maintained:
Yes
Name:
Sequence, Structure and Conservation profiler
Restrictions to use:
None
Stability:
Stable

Credits

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Publications

Institution(s)

Institute of Molecular Biology and Biotechnology-FORTH, Heraklion, University of Crete, Heraklion, Greece

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