DISOPRED3: precise disordered region predictions with annotated protein-binding activity | Zendy

David T. Jones | Zendy; Domenico Cozzetto | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

DISOPRED3: precise disordered region predictions with annotated protein-binding activity

Author(s) -

David T. Jones,

Domenico Cozzetto

Publication year - 2014

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/btu744

Subject(s) - intrinsically disordered proteins , computer science , classifier (uml) , sequence (biology) , computational biology , casp , protein methods , support vector machine , identification (biology) , protein structure , data mining , peptide sequence , artificial intelligence , protein structure prediction , biology , genetics , biochemistry , gene , botany

A sizeable fraction of eukaryotic proteins contain intrinsically disordered regions (IDRs), which act in unfolded states or by undergoing transitions between structured and unstructured conformations. Over time, sequence-based classifiers of IDRs have become fairly accurate and currently a major challenge is linking IDRs to their biological roles from the molecular to the systems level.

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