@article{7037a2e9fb914f7c813fecc0e20f8f9d,
title = "Feature Reduction for Molecular Similarity Searching Based on Autoencoder Deep Learning",
keywords = "autoencoder, drug design, irrelevant and redundant features, molecular similarity",
author = "Maged Nasser and Naomie Salim and Faisal Saeed and Shadi Basurra and Idris Rabiu and Hentabli Hamza and Alsoufi, {Muaadh A.}",
note = "Funding Information: Funding: This research was funded by Research Management Center (RMC) at the Universiti Teknologi Malaysia (UTM) under the Research University Grant Category (VOT Q.J130000.2528.16H74, Q.J130000.2528.18H56, and R.J130000.7828.4F985) and funded by the Data Analytics and Artificial Intelligence (DAAI), Birmingham City University, UK. Funding Information: Acknowledgments: This work is supported by the Ministry of Higher Education (MOHE) and the Research Management Center (RMC) at the Universiti Teknologi Malaysia (UTM) under the Research University Grant Category (VOT Q.J130000.2528.16H74, Q.J130000.2528.18H56, and R.J130000.7828.4F985) and funded by the Data Analytics and Artificial Intelligence (DAAI) research group, Birmingham City University, UK. Publisher Copyright: {\textcopyright} 2022 by the authors. Licensee MDPI, Basel, Switzerland.",
year = "2022",
month = mar,
day = "27",
doi = "10.3390/biom12040508",
language = "English",
volume = "12",
journal = "Biomolecules",
issn = "2218-273X",
publisher = "MDPI",
number = "4",
}