An Evaluation on Different Machine Learning Algorithms for Classification and Prediction of Antifungal Peptides.
Journal:
Medicinal chemistry (Shariqah (United Arab Emirates))
Published Date:
Jan 1, 2016
Abstract
BACKGROUND: Fungi are an emerging threat in medicine and agriculture and current therapeutics have proved to be insufficient and toxic. This has led to an increased interest in peptide-based therapeutics, especially antifungal peptides (AFPs), being safer and more effective drug candidates against fungal threats. However, screening for peptides with antifungal activity is costly and timeconsuming. However, by using computational techniques, we can overcome these restricting factors. The aim of the present study is to compare different machine learning algorithms in combination with Chou's pseudo amino acid composition in classifying and predicting AFPs to represent a precise model for AFP prediction.