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- Currently displaying 81 - 100 of 562 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)
Chapter 8 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.
J Med Chem
(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
Molecular pharmaceutics
(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
Journal of cheminformatics
(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.
Comput Toxicol
(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)
Relating early cellular events to Drug-Induced Liver Injury (DILI) using time-resolved transcriptomic and histopathology data
Toxicology Letters
(2021)
350
s124
The impact of pooling animal histopathology control data on the statistical detection of treatment-related findings
Toxicology Letters
(2021)
350
S63
A transcriptomics-based new approach methodology (NAM) identifies points of departure (PoDs) of adaptive stress in HepG2 cells
TOXICOLOGY LETTERS
(2021)
350
S216
Cell morphology descriptors and gene ontology profiles improve prediction for mitochondrial toxicity
Toxicology Letters
(2021)
350
S81
Prediction of inotropic effect based on calcium transients in human iPSC-derived cardiomyocytes using novel waveform parameters and a modified random forest algorithm
TOXICOLOGY LETTERS
(2021)
350
S61
Artificial Intelligence in Drug Discovery and Computational Safety: What is Realistic, What are Illusions?
TOXICOLOGY LETTERS
(2021)
350
S49