Universal evolutionary selection for high dimensional silent patterns of information hidden in the redundancy of viral genetic code | Zendy

Eli Goz | Zendy; Zohar Zafrir | Zendy; Tamir Tuller | Zendy

Open Access

Universal evolutionary selection for high dimensional silent patterns of information hidden in the redundancy of viral genetic code

Author(s) -

Eli Goz,

Zohar Zafrir,

Tamir Tuller

Publication year - 2018

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/bty351

Subject(s) - substring , genetic code , biology , viral evolution , codon usage bias , gene , computational biology , genetics , redundancy (engineering) , selection (genetic algorithm) , fitness landscape , host (biology) , genome , computer science , artificial intelligence , population , demography , set (abstract data type) , sociology , programming language , operating system

Understanding how viruses co-evolve with their hosts and adapt various genomic level strategies in order to ensure their fitness may have essential implications in unveiling the secrets of viral evolution, and in developing new vaccines and therapeutic approaches. Here, based on a novel genomic analysis of 2625 different viruses and 439 corresponding host organisms, we provide evidence of universal evolutionary selection for high dimensional 'silent' patterns of information hidden in the redundancy of viral genetic code.

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