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AMALPHI: A Machine Learning Platform for Predicting Drug-In..:

Maria Cristina Lomuscio ; Carmen Abate ; Domenico Alberga...
doi:10.1021/acs.molpharmaceut.3c00964.s003. , 2024

Link: https://doi.org/10.1021/acs.molpharmaceut.3c00964.s003

RT Journal
T1 <Title>AMALPHI: A Machine Learning Platform for Predicting Drug-Induced PhospholIpidosis</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftunivoxfordfig:oai:figshare.com:article_24898329&Exemplar=1&LAN=DE
				
A1 Maria Cristina Lomuscio
A1 Carmen Abate
A1 Domenico Alberga
A1 Antonio Laghezza
A1 Nicola Corriero
A1 Nicola Antonio Colabufo
A1 Michele Saviano
A1 Pietro Delre
A1 Giuseppe Felice Mangiatordi
YR 2024
K1 Biochemistry
K1 Medicine
K1 Pharmacology
K1 Biotechnology
K1 Mental Health
K1 Biological Sciences not elsewhere classified
K1 Chemical Sciences not elsewhere classified
K1 Information Systems not elsewhere classified
K1 vitro antiviral activity
K1 particularly within lysosomes
K1 medicinal chemists interested
K1 made freely available
K1 machine learning platform
K1 machine learning classifiers
K1 https :// www
K1 confounding antiviral data
K1 auc value computed
K1 achieved high performance
K1 545 </ b
K1 pld inducer potential
K1 induced phospholipidosis drug
K1 induced phospholipidosis
K1 inducing potential
K1 drug repurposing
K1 drug candidates
K1 valuable tool
K1 significant portion
K1 prolonged exposure
K1 pld affects
K1 obtained using
K1 multiple tissues
K1 may lead
K1 early evaluation
K1 drugs currently
K1 druglike compounds
K1 chembl v30
K1 cads )
K1 become crucial
K1 amalphiportal /)
JF doi:10.1021/acs.molpharmaceut.3c00964.s003
LK http://dx.doi.org/https://doi.org/10.1021/acs.molpharmaceut.3c00964.s003
DO https://doi.org/10.1021/acs.molpharmaceut.3c00964.s003
SF ELIB - SuUB Bremen

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