Co-AMPpred for in silico-aided predictions of antimicrobial peptides by integrating composition-based features

Co-AMPpred for in silico-aided predictions of antimicrobial peptides by integrating composition-based features

Background: Antimicrobial peptides (AMPs) are oligopeptides that act as crucial components of innate immunity, naturally occur in all multicellular organisms, and are involved in the first line of defense function. Recent studies showed that AMPs perpetuate great potential that is not limited to ant...

Full description

Bibliographic Details
Main Authors: Hsu, W.-L (Author), Singh, O. (Author), Su, E.C.-Y (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
algorithm
Algorithms
Amino acid composition
Antibiotics
Anti-microbial activity
Antimicrobial peptide
Benchmarking
Bioinformatics
Cell death
Compositional features
Composition-based feature
computer simulation
Computer Simulation
Cross-validation technique
Feature selection algorithm
Forecasting
Immune system
Learning algorithms
machine learning
Machine learning
Machine Learning
Microorganisms
Multicellular organisms
Peptides
Physicochemical features
pore forming cytotoxic protein
Pore Forming Cytotoxic Proteins
Predictive analytics
Predictive performance
receiver operating characteristic
Receiver operating characteristic curves
ROC Curve
Statistical tests
Tissue regeneration
Online Access:View Fulltext in Publisher

Internet

View Fulltext in Publisher

Similar Items