RNAsnoop: efficient target prediction for H/ACA snoRNAs | Zendy

Hakim Tafer | Zendy; Stephanie Kehr | Zendy; Jana Hertel | Zendy; Ivo L. Hofacker | Zendy; Peter F. Stadler | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

RNAsnoop: efficient target prediction for H/ACA snoRNAs

Author(s) -

Hakim Tafer,

Stephanie Kehr,

Jana Hertel,

Ivo L. Hofacker,

Peter F. Stadler

Publication year - 2009

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btp680

Subject(s) - small nucleolar rna , computational biology , rna , computer science , pseudouridine , biology , transfer rna , non coding rna , genetics , gene

Small nucleolar RNAs are an abundant class of non-coding RNAs that guide chemical modifications of rRNAs, snRNAs and some mRNAs. In the case of many 'orphan' snoRNAs, the targeted nucleotides remain unknown, however. The box H/ACA subclass determines uridine residues that are to be converted into pseudouridines via specific complementary binding in a well-defined secondary structure configuration that is outside the scope of common RNA (co-)folding algorithms.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research