PeptideLocator: prediction of bioactive peptides in protein sequences | Zendy

Catherine Mooney | Zendy; Niall Haslam | Zendy; Thérèse A. Holton | Zendy; Gianluca Pollastri | Zendy; Denis C. Shields | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

PeptideLocator: prediction of bioactive peptides in protein sequences

Author(s) -

Catherine Mooney,

Niall Haslam,

Thérèse A. Holton,

Gianluca Pollastri,

Denis C. Shields

Publication year - 2013

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/btt103

Subject(s) - computational biology , peptide , computer science , training set , redundancy (engineering) , protein sequencing , peptide sequence , biology , bioinformatics , machine learning , artificial intelligence , biochemistry , gene , operating system

Peptides play important roles in signalling, regulation and immunity within an organism. Many have successfully been used as therapeutic products often mimicking naturally occurring peptides. Here we present PeptideLocator for the automated prediction of functional peptides in a protein sequence.

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