title: Computational prediction of viral miRNAs.
abstract: While cloning and/or massive parallel sequencing of small RNAs represent powerful tools for the discovery of novel miRNAs, computational miRNA prediction represents a valuable alternative which can be performed with comparably little technical effort. This is especially true for viruses, as the number of predicted candidates generally remains low and thus within a range that may be readily confirmed by experimental means. Here, we provide a detailed protocol for the prediction of putative miRNA genes using VMir, an ab initio prediction program which we have recently designed specifically to identify pre-miRNAs in viral genomes.
authors: Heinrich-Pette-Institute for Experimental Virology and Immunology, Hamburg, Germany. Adam.Grundhoff@hpi.uni-hamburg.de
authors: Adam
authors: A
authors: Grundhoff
mesh_terms: D015152:Blotting, Northern; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D035683:MicroRNAs / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D012367:RNA, Viral / Q000235:genetics*; D014584:User-Computer Interface; D014780:Viruses / Q000235:genetics*
chemical_list: D035683:MicroRNAs; D012367:RNA, Viral