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- Currently displaying 81 - 100 of 561 publications
DILIC: An AI based classifier to search for Drug-Induced Liver Injury literature
(2022)
2022.02.12.480184
(doi: 10.1101/2022.02.12.480184)
Deriving waveform parameters from calcium transients in human iPSC-derived cardiomyocytes to predict cardiac activity with machine learning
Stem Cell Reports
(2022)
17
556
(doi: 10.1016/j.stemcr.2022.01.009)
DDREL: From drug-drug relationships to drug repurposing
Intelligent Data Analysis
(2022)
26
221
(doi: 10.3233/ida-215745)
Integrating Cell Morphology with Gene Expression and Chemical Structure to Aid Mitochondrial Toxicity Detection
biorxiv
(2022)
2022.01.07.475326
(doi: 10.1101/2022.01.07.475326)
Using Artificial Intelligence for Drug Repurposing
(2022)
2022-January
147
(doi: 10.1039/9781839163401-00147)
Virtual Screening Directly Identifies New Fragment-Sized Inhibitors of Carboxylesterase Notum with Nanomolar Activity
Journal of medicinal chemistry
(2021)
65
562
(doi: 10.1021/acs.jmedchem.1c01735)
Computational analyses of mechanism of action (MoA): data, methods and integration.
RSC Chemical Biology
(2021)
3
170
(doi: 10.1039/d1cb00069a)
Machine Learning Models for Human In Vivo Pharmacokinetic Parameters with In-House Validation
Mol Pharm
(2021)
18
4520
Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges
Methods Mol Biol
(2021)
2390
1
(doi: 10.1007/978-1-0716-1787-8_1)
Synergy conformal prediction applied to large-scale bioactivity datasets and in federated learning
J Cheminform
(2021)
13
77
(doi: 10.1186/s13321-021-00555-7)
Deriving time-concordant event cascades from gene expression data: A case study for Drug-Induced Liver Injury (DILI)
(2021)
2021.09.23.461089
(doi: 10.1101/2021.09.23.461089)
In silico approaches in organ toxicity hazard assessment: Current status and future needs for predicting heart, kidney and lung toxicities.
Computational Toxicology
(2021)
20
100188
(doi: 10.1016/j.comtox.2021.100188)
In silico approaches in organ toxicity hazard assessment: current status and future needs in predicting liver toxicity.
Computational toxicology (Amsterdam, Netherlands)
(2021)
20
100187
(doi: 10.1016/j.comtox.2021.100187)
Prediction and identification of synergistic compound combinations against pancreatic cancer cells.
iScience
(2021)
24
103080
(doi: 10.1016/j.isci.2021.103080)
The impact of pooling animal histopathology control data on the statistical detection of treatment-related findings
Toxicology Letters
(2021)
350
s63
Cell morphology descriptors and gene ontology profiles improve prediction for mitochondrial toxicity
Toxicology Letters
(2021)
350
S81
Relating early cellular events to Drug-Induced Liver Injury (DILI) using time-resolved transcriptomic and histopathology data
Toxicology Letters
(2021)
350
s124
Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty.
Journal of Cheminformatics
(2021)
13
62
(doi: 10.1186/s13321-021-00539-7)
Structural Insights into Notum Covalent Inhibition.
J Med Chem
(2021)
64
11354
(doi: 10.1021/acs.jmedchem.1c00701)
Identification of SARS-CoV-2-induced pathways reveals drug repurposing strategies
Sci Adv
(2021)
7
eabh3032
(doi: 10.1126/sciadv.abh3032)