Machine Learning Study of Metabolic Networks vs ChEMBL Data of Antibacterial Compounds

Machine Learning Study of Metabolic Networks vs ChEMBL Data of Antibacterial Compounds

Antibacterial drugs (AD) change the metabolic status of bacteria, contributing to bacterial death. However, antibiotic resistance and the emergence of multidrug-resistant bacteria increase interest in understanding metabolic network (MN) mutations and the interaction of AD vs MN. In this study, we e...

詳細記述

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書誌詳細
第一著者: Diéguez Santana, Karel (author)
その他の著者: Casañola Martin, Gerardo M (author), Torres Gutiérrez, Roldán (author), Rasulev, Bakhtiyor (author), R Green, James (author), González-Díaz, Humbert (author)
フォーマット: article
出版事項: 2022
主題:
ChEMBL; antibacterial compounds
Complex networks
Information fusion
Machine learning
Multidrug-resistant
Perturbation theory.
オンライン･アクセス:https://doi.org/10.1021/acs.molpharmaceut.2c00029
http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/580
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https://doi.org/10.1021/acs.molpharmaceut.2c00029
http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/580

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