Ambivalent covariance models.

ABSTRACT:

Background

Evolutionary variations let us define a set of similar nucleic acid sequences as a family if these different molecules execute a common function. Capturing their sequence variation by using e. g. position specific scoring matrices significantly improves sensitivity of detection tools. Members of a functional (non-coding) RNA family are affected by these variations not only on the sequence, but also on the structural level. For example, some transfer-RNAs exhibit a fifth helix in addition to the typical cloverleaf structure. Current covariance models - the unrivaled homology search approach for structured RNA - do not benefit from structural variation within a family, but rather penalize it. This leads to artificial subdivision of families and loss of information in the R

SUBMITTER: Janssen S 

PROVIDER: S-EPMC4504443 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature