[HTML][HTML] Network biology and artificial intelligence drive the understanding of the multidrug resistance phenotype in cancer
B Bueschbell, AB Caniceiro, PMS Suzano… - Drug Resistance …, 2022 - Elsevier
Globally with over 10 million deaths per year, cancer is the most transversal disease across
countries, cultures, and ethnicities, affecting both developed and developing regions …
countries, cultures, and ethnicities, affecting both developed and developing regions …
Computational approaches in cancer multidrug resistance research: Identification of potential biomarkers, drug targets and drug-target interactions
Like physics in the 19th century, biology and molecular biology in particular, has been
fertilized and enhanced like few other scientific fields, by the incorporation of mathematical …
fertilized and enhanced like few other scientific fields, by the incorporation of mathematical …
ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning
Breast cancer resistance protein (BCRP/ABCG2), an ATP-binding cassette (ABC) efflux
transporter, plays a critical role in multi-drug resistance (MDR) to anti-cancer drugs and drug …
transporter, plays a critical role in multi-drug resistance (MDR) to anti-cancer drugs and drug …
Machine learning models for classification tasks related to drug safety
In this review, we outline the current trends in the field of machine learning-driven
classification studies related to ADME (absorption, distribution, metabolism and excretion) …
classification studies related to ADME (absorption, distribution, metabolism and excretion) …
Machine Learning Techniques Applied to the Study of Drug Transporters
X Kong, K Lin, G Wu, X Tao, X Zhai, L Lv, D Dong… - Molecules, 2023 - mdpi.com
With the advancement of computer technology, machine learning-based artificial
intelligence technology has been increasingly integrated and applied in the fields of …
intelligence technology has been increasingly integrated and applied in the fields of …
9-Deazapurines as broad-spectrum inhibitors of the ABC transport proteins P-glycoprotein, multidrug resistance-associated protein 1, and breast cancer resistance …
P-Glycoprotein (P-gp, ABCB1), multidrug resistance-associated protein 1 (MRP1, ABCC1),
and breast cancer resistance protein (BCRP, ABCG2) are the three major ABC transport …
and breast cancer resistance protein (BCRP, ABCG2) are the three major ABC transport …
A model for identifying potentially inappropriate medication used in older people with dementia: a machine learning study
Q Hu, M Zhao, F Teng, G Lin, Z Jin, T Xu - International Journal of Clinical …, 2024 - Springer
Background Older adults with dementia often face the risk of potentially inappropriate
medication (PIM) use. The quality of PIM evaluation is hindered by researchers' unfamiliarity …
medication (PIM) use. The quality of PIM evaluation is hindered by researchers' unfamiliarity …
In Silico Prediction of Endocrine Disrupting Chemicals Using Single-Label and Multilabel Models
L Sun, H Yang, Y Cai, W Li, G Liu… - Journal of chemical …, 2019 - ACS Publications
Endocrine disruption (ED) has become a serious public health issue and also poses a
significant threat to the ecosystem. Due to complex mechanisms of ED, traditional in silico …
significant threat to the ecosystem. Due to complex mechanisms of ED, traditional in silico …
Prediction of activity and selectivity profiles of human Carbonic Anhydrase inhibitors using machine learning classification models
A Tinivella, L Pinzi, G Rastelli - Journal of Cheminformatics, 2021 - Springer
The development of selective inhibitors of the clinically relevant human Carbonic Anhydrase
(hCA) isoforms IX and XII has become a major topic in drug research, due to their …
(hCA) isoforms IX and XII has become a major topic in drug research, due to their …
Ligand-and structure-based drug design and optimization using KNIME
MP Mazanetz, CHF Goode… - Current medicinal …, 2020 - ingentaconnect.com
In recent years there has been a paradigm shift in how data is being used to progress early
drug discovery campaigns from hit identification to candidate selection. Significant …
drug discovery campaigns from hit identification to candidate selection. Significant …