Utilizing machine learning techniques to predict the blood-brain barrier permeability of compounds detected using LCQTOF-MS in Malaysian Kelulut honey-Reference-Cited by-同舟云学术

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Utilizing machine learning techniques to predict the blood-brain barrier permeability of compounds detected using LCQTOF-MS in Malaysian Kelulut honey

Published:2023-06-03 Issue:6 Volume:34 Page:475-500
ISSN:1062-936X
Container-title:SAR and QSAR in Environmental Research
language:en
Short-container-title:SAR and QSAR in Environmental Research

Author:

Edros R.¹²^ORCID,Feng T.W.¹^ORCID,Dong R.H.³^ORCID

Affiliation:

1. Faculty of Chemical and Process Engineering Technology, Universiti Malaysia Pahang, Gambang, Malaysia

2. Centre for Advanced Research in Fluid Flow, Universiti Malaysia Pahang, Gambang, Malaysia

3. The Insight Centre for Data Analytics, School of Computer Science, University College Dublin, Dublin, Ireland

Funder

Universiti Malaysia Pahang

Ministry of Education Malaysia

Publisher

Informa UK Limited

Subject

Drug Discovery,Molecular Medicine,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/1062936X.2023.2230868

Reference106 articles.

1. Artificial intelligence-enhanced drug design and development: Toward a computational precision medicine

2. Evaluation of biogenic nanosilver-acticoat for wound healing: A tri-modal in silico, in vitro and in vivo study

3. Machine learning for precision medicine

4. Combinatorial Drug Discovery from Activity-Related Substructure Identification

5. Valency-based topological descriptors of chemical networks and their applications

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