Deep Learning Algorithms Identify Structures in Living Cells

Researchers are using artificial intelligence to pick out the features of brightfield microscopy images.

Written byDiana Kwon
| 4 min read
images taken with brightfield microscopy

Register for free to listen to this article
Listen with Speechify
0:00
4:00
Share

ABOVE: MODIFIED FROM THE ALLEN INSTITUTE

For cell biologists, fluorescence micro­scopy is an invaluable tool. Fusing dyes to antibodies or inserting genes coding for fluorescent proteins into the DNA of living cells can help scientists pick out the location of organelles, cytoskeletal elements, and other subcellular structures from otherwise impenetrable microscopy images. But this technique has its drawbacks. There are limits to the number of fluorescent tags that can be introduced into a cell, and side effects such as photo­toxicity—damage caused by repeated exposure to light—can hinder researchers’ ability to conduct live cell imaging.

These issues were on biomedical engineer Greg Johnson’s mind when he joined the Allen Institute for Cell Science in Seattle in 2016. Johnson, whose doctoral work at Carnegie Mellon University had focused on creating computational tools to model cellular structures (see “Robert Murphy Bets Self Driving Instruments Will Crack Biology's Mysteries” here), was hired as part ...

Interested in reading more?

Become a Member of

The Scientist Logo
Receive full access to digital editions of The Scientist, as well as TS Digest, feature stories, more than 35 years of archives, and much more!
Already a member? Login Here

Related Topics

Meet the Author

  • Diana is a freelance science journalist who covers the life sciences, health, and academic life. She’s a regular contributor to The Scientist and her work has appeared in several other publications, including Scientific American, Knowable, and Quanta. Diana was a former intern at The Scientist and she holds a master’s degree in neuroscience from McGill University. She’s currently based in Berlin, Germany.

    View Full Profile

Published In

May 2019 The Scientist Issue
May 2019

AI Tackles Biology

How machine learning will revolutionize science and medicine.

Share
February 2026

A Stubborn Gene, a Failed Experiment, and a New Path

When experiments refuse to cooperate, you try again and again. For Rafael Najmanovich, the setbacks ultimately pushed him in a new direction.

View this Issue
Human-Relevant In Vitro Models Enable Predictive Drug Discovery

Advancing Drug Discovery with Complex Human In Vitro Models

Stemcell Technologies
Redefining Immunology Through Advanced Technologies

Redefining Immunology Through Advanced Technologies

Ensuring Regulatory Compliance in AAV Manufacturing with Analytical Ultracentrifugation

Ensuring Regulatory Compliance in AAV Manufacturing with Analytical Ultracentrifugation

Beckman Coulter Logo
Conceptual multicolored vector image of cancer research, depicting various biomedical approaches to cancer therapy

Maximizing Cancer Research Model Systems

bioxcell

Products

Sino Biological Logo

Sino Biological Pioneers Life Sciences Innovation with High-Quality Bioreagents on Inside Business Today with Bill and Guiliana Rancic

Sino Biological Logo

Sino Biological Expands Research Reagent Portfolio to Support Global Nipah Virus Vaccine and Diagnostic Development

Beckman Coulter

Beckman Coulter Life Sciences Partners with Automata to Accelerate AI-Ready Laboratory Automation

Refeyn logo

Refeyn named in the Sunday Times 100 Tech list of the UK’s fastest-growing technology companies