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

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

Current in silico modelling techniques, such as molecular dynamics, typically focus on compounds with the highest concentration from chromatographic analyses for bioactivity screening. Consequently, they reduce the need for labour-intensive in vitro studies but limit the utilization of extensive chr...

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Bibliographic Details
Main Authors: Raihana Zahirah, Edros, Feng, Tan wei, Dong, RuiHai
Format: Article
Language:English
English
Published: Taylor & Francis 2023
Subjects:
T Technology (General)
TP Chemical technology
Online Access:http://umpir.ump.edu.my/id/eprint/42715/
http://umpir.ump.edu.my/id/eprint/42715/1/Utilizing%20machine%20learning%20techniques%20to%20predict%20the%20blood%20brain%20barrier%20permeability%20of%20compounds%20detected%20using%20LCQTOF%20MS%20in%20Malaysian%20Kelulut.pdf
http://umpir.ump.edu.my/id/eprint/42715/2/Utilizing%20machine%20learning%20techniques%20to%20predict%20the%20blood%20brain%20barrier%20permeability%20of%20compounds%20detected%20using%20LCQTOF%20MS%20in%20Malaysian%20Kelulut%20honey.pdf

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