Amanote Research
Register
Sign In
Drug Discovery Maps, a Machine Learning Model That Visualizes and Predicts KinomeInhibitor Interaction Landscapes
doi 10.1021/acs.jcim.8b00640.s002
Full Text
Open PDF
Abstract
Available in
full text
Date
Unknown
Authors
Unknown
Publisher
American Chemical Society (ACS)
Related search
Machine Learning Technique Approaches in Drug Discovery, Design and Development
Information Technology Journal
Machine Learning Predicts New Anti-Crispr Proteins
Machine Learning: From Radiomics to Discovery and Routine
Der Radiologe
Nuclear Medicine
Radiology
Imaging
Machine-Learning Guided Discovery of a New Thermoelectric Material
Scientific Reports
Multidisciplinary
Targeting Historically Refractory Interfaces: A Partnership Model That Accelerates Drug Discovery Within an Expanded Haystack
Future Medicinal Chemistry
Drug Discovery
Molecular Medicine
Pharmacology
Yeast as a Model System for Drug Discovery
Folia Pharmacologica Japonica
Pharmacology
Generating Customized Compound Libraries for Drug Discovery With Machine Intelligence
Traditional Drug-Discovery Model Ripe for Reform
Nature
Multidisciplinary
Sharpening Up Galactic All-Sky Maps With Complementary Data. A Machine Learning Approach
Astronomy and Astrophysics
Astrophysics
Astronomy
Planetary Science
Space