Integrating transformer and imbalanced multi-label learning to identify antimicrobial peptides and their functional activities
Sign Up to like & getrecommendations! Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btac711
Abstract: Abstract Motivation Antimicrobial peptides (AMPs) have the potential to inhibit multiple types of pathogens and to heal infections. Computational strategies can assist in characterizing novel AMPs from proteome or collections of synthetic sequences and discovering… read more here.
Keywords: integrating transformer; multi label; antimicrobial peptides; functional activities ... See more keywords
Integrating Transformer and Autoencoder Techniques with Spectral Graph Algorithms for the Prediction of Scarcely Labeled Molecular Data
Sign Up to like & getrecommendations! Published in 2022 at "Computers in biology and medicine"
DOI: 10.48550/arxiv.2211.06759
Abstract: In molecular and biological sciences, experiments are expensive, time-consuming, and often subject to ethical constraints. Consequently, one often faces the challenging task of predicting desirable properties from small data sets or scarcely-labeled data sets. Although… read more here.
Keywords: scarcely labeled; transformer autoencoder; labeled data; integrating transformer ... See more keywords