MultiPep: a hierarchical deep learning approach for multi-label classification of peptide bioactivities.

ABSTRACT: Peptide-based therapeutics are here to stay and will prosper in the future. A key step in identifying novel peptide-drugs is the determination of their bioactivities. Recent advances in peptidomics screening approaches hold promise as a strategy for identifying novel drug targets. However, these screenings typically generate an immense number of peptides and tools for ranking these peptides prior to planning functional studies are warranted. Whereas a couple of tools in the literature predict multiple classes, these are constructed using multiple binary classifiers. We here aimed to use an innovative deep learning approach to generate an improved peptide bioactivity classifier with capacity of distinguishing between multiple classes. We present MultiPep: a deep learning multi-label classif

SUBMITTER: Gronning AGB 

PROVIDER: S-EPMC8665375 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature