Qsar model for predicting neuraminidase inhibitors of influenza a viruses (H1N1) based on adaptive grasshopper optimization algorithm

• Main Authors: Algamal, Zakariya Y., Qasim, Maimoonah Khalid, Lee, Muhammad Hisyam, Mohammad Ali, Haithem Taha
• Format: Article
• Published: Taylor and Francis Ltd. 2020
• Subjects: Q Science (General)
• Online Access: http://eprints.utm.my/id/eprint/90315/; http://dx.doi.org/10.1080/1062936X.2020.1818616
• Institution: Universiti Teknologi Malaysia

High-dimensionality is one of the major problems which affect the quality of the quantitative structure–activity relationship (QSAR) modelling. Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a ne...