YoVDO

Cell Morphology-Guided De Novo Hit Design by Conditioning GANs on Phenotypic Image Features

Offered By: Valence Labs via YouTube

Tags

Drug Discovery Courses Machine Learning Courses Computational Chemistry Courses Cheminformatics Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a groundbreaking approach to de novo hit design in drug discovery through a 49-minute talk on cell morphology-guided molecule generation using conditional GANs. Learn how cellular morphology data can directly inform the creation of novel bioactive compounds, potentially revolutionizing the time-consuming and costly process of drug development. Discover the methodology behind training a generative model on 30,000 compounds using cell painting morphological profiles as conditioning factors. Examine evidence for targeted generation of known agonists based on gene overexpression profiles, despite the absence of explicit biological target information during training. Delve into model evaluation, interpolation experiments, and the potential for this target-agnostic approach to facilitate knowledge transfer between biological pathways. Gain insights into the future applications of this proof-of-concept for hit generation in drug and phytopharmaceutical discovery, as well as chemical safety assessment.

Syllabus

- Intro
- Using Profiling Technologies to Guide the Design of Small Molecules
- Model Evaluation
- Can the Model Generate Bioactives for Specific Targets?
- Interpolation Experiments
- Conclusion & Outlook
- Q&A


Taught by

Valence Labs

Related Courses

The Quantum World
Harvard University via edX
Approximate Methods In Quantum Chemistry
Indian Institute of Technology, Kharagpur via Swayam
Computational Chemistry and Classical Molecular Dynamics
NPTEL via YouTube
A Mathematical Look at Electronic Structure Theory - JuliaCon 2021 Workshop
The Julia Programming Language via YouTube
Breaking the Curse of Dimension in Quantum Mechanical Computations Through Analysis and Probability
Alan Turing Institute via YouTube