YoVDO

Finding Disease Phenotypes and Candidate Therapeutics Using Images: Cell Painting

Offered By: Broad Institute via YouTube

Tags

Bioinformatics Courses Machine Learning Courses Drug Discovery Courses Computational Biology Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore large-scale imaging experiments and image-based profiling techniques in this 42-minute talk by Anne Carpenter and Shantanu Singh from the Broad Institute. Learn about Cell Painting, a method for creating visual signatures of genes, compounds, and diseases. Discover how to identify differences between diseased and healthy cells, cluster genes based on morphological similarities, and predict small molecule mechanisms of action. Delve into the potential of morphological profiling for virtual screening, predicting assay readouts, and transforming biomedical challenges into machine learning problems.

Syllabus

Intro
Large-scale imaging experiments
Image-based profiling: use images to create signatures of genes, compounds and diseases
What is image-based profiling via Cell Painting?
Identify a difference between diseased and healthy cells
Identifying disease phenotypes by image-based profiling
Genes cluster based on morphological similarity
Identifying chemical regulators of genes by virtual screen
Morphological profiling can predict small molecule mechanism of action
Can we predict assay readouts for compounds using image data?
Predicting many cell health assays from Cell Painting
Cell Painting: Biomedicine problems machine learning problems?


Taught by

Broad Institute

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity
Natural Language Processing
Columbia University via Coursera
Probabilistic Graphical Models 1: Representation
Stanford University via Coursera
Computer Vision: The Fundamentals
University of California, Berkeley via Coursera
Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent