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- Currently displaying 241 - 260 of 574 publications
In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts
Frontiers in Chemistry
(2018)
6
30
(doi: 10.3389/fchem.2018.00030)
Common structural and pharmacophoric features of mPGES-1 and LTC4S.
Future medicinal chemistry
(2018)
10
259
(doi: 10.4155/fmc-2017-0123)
In silico estimation of chemical aquatic toxicity on crustaceans using chemical category methods.
Environmental Science Processes & Impacts
(2018)
20
1234
(doi: 10.1039/c8em00220g)
Gearing transcriptomics towards high-throughput screening: Compound shortlisting from gene expression using in silico information
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Analysing matched molecular pair transformations in drug discovery projects as a function of time and molecular environment
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Binding mode ensembles determine ligand efficacy at a GPCR
NAUNYN-SCHMIEDEBERGS ARCHIVES OF PHARMACOLOGY
(2018)
391
S6
Understanding drug and compound combinations and modelling synergy - Methods and applications
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Computational selectivity modelling for bromodomains: Insights into selectivity and discovery of new small-molecule hits
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Artificial intelligence for predicting molecular electrostatic potentials (ESPs): A step towards developing ESP-guided knowledge-based scoring functions
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
MD-assisted approach for designing multi-target ligands at A2AR and PDE10A that elevate cyclic AMP
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Information-derived adverse outcome pathways with a case study on structural cardiotoxicity
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Determining associations between transcriptomics and toxicity using co-expression network methods
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Understanding the effect of arsenic treatment on breast cancer cell lines using gene expression analysis
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Developments in toxicogenomics: Understanding and predicting compound-induced toxicity from gene expression data
Molecular omics
(2018)
14
218
(doi: 10.1039/c8mo00042e)
Computer-aided design of multi-target ligands at A
J Cheminform
(2017)
9
67
(doi: 10.1186/s13321-017-0249-4)
Identification of Novel Aurora Kinase A (AURKA) Inhibitors via Hierarchical Ligand-Based Virtual Screening.
Journal of chemical information and modeling
(2017)
58
36
(doi: 10.1021/acs.jcim.7b00300)
In silico prediction of chemical genotoxicity using machine learning methods and structural alerts.
Toxicol Res (Camb)
(2017)
7
211
(doi: 10.1039/c7tx00259a)
DeepSynergy: Predicting anti-cancer drug synergy with Deep Learning
Bioinformatics
(2017)
34
1538
Innovation in Small-Molecule-Druggable Chemical Space: Where are the Initial Modulators of New Targets Published?
Journal of Chemical Information and Modeling
(2017)
60
3902
Innovation in Small-Molecule-Druggable Chemical Space: Where are the Initial Modulators of New Targets Published?
Journal of Chemical Information and Modeling
(2017)
57
2741
(doi: 10.1021/acs.jcim.7b00295)
