Syotti: scalable bait design for DNA enrichment | Zendy

Jarno Alanko | Zendy; Ilya B. Slizovskiy | Zendy; Daniel Lokshtanov | Zendy; Travis Gagie | Zendy; Noelle Noyes | Zendy; Christina Boucher | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Syotti: scalable bait design for DNA enrichment

Author(s) -

Jarno Alanko,

Ilya B. Slizovskiy,

Daniel Lokshtanov,

Travis Gagie,

Noelle Noyes,

Christina Boucher

Publication year - 2022

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/btac226

Subject(s) - metagenomics , scalability , computer science , heuristic , set (abstract data type) , computational biology , dna , process (computing) , protocol (science) , data mining , algorithm , biology , database , genetics , artificial intelligence , programming language , gene , medicine , alternative medicine , pathology

Bait enrichment is a protocol that is becoming increasingly ubiquitous as it has been shown to successfully amplify regions of interest in metagenomic samples. In this method, a set of synthetic probes ('baits') are designed, manufactured and applied to fragmented metagenomic DNA. The probes bind to the fragmented DNA and any unbound DNA is rinsed away, leaving the bound fragments to be amplified for sequencing. Metsky et al. demonstrated that bait-enrichment is capable of detecting a large number of human viral pathogens within metagenomic samples.

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