Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

An integrated single-cell and spatial proteotranscriptomics atlas of fibroblast-driven immunoregulation within the human adult oral cavity.

Cell press blue·2026

Same author

Spatial proteomic analysis in human Alzheimer's disease brains enables identification of microenvironment-dependent microglial cell states.

Nature neuroscience·2026

Same author

Progress and new challenges in image-based profiling.

Molecular systems biology·2026

Same author

Cell-DINO: Self-supervised image-based embeddings for cell fluorescent microscopy.

PLoS computational biology·2025

Same author

Progress and new challenges in image-based profiling.

ArXiv·2025

Same author

Synthesizing late-stage contrast enhancement in breast MRI: A comprehensive pipeline leveraging temporal contrast enhancement dynamics.

Computers in biology and medicine·2025

Same journal

Function through shape: An overview of DNA G-quadruplexes in transcriptional regulation.

Current opinion in chemical biology·2026

Same journal

Advances in tools and technologies for multiplexed bioluminescence imaging.

Current opinion in chemical biology·2026

Same journal

High-resolution molecular mapping by expansion-coupled label-free and multimodal imaging.

Current opinion in chemical biology·2026

Same journal

Recent advances in glycoconjugate-based therapeutics.

Current opinion in chemical biology·2026

Same journal

Towards better red emitters for bioimaging: Innovations in rhodamine and cyanine chemistry.

Current opinion in chemical biology·2026

Same journal

Chemigenetic fluorescent biosensors in biological imaging - New trends and advances.

Current opinion in chemical biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Nov 4, 2025

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Published on: October 4, 2024

Image-based cell phenotyping with deep learning.

Aditya Pratapa¹, Michael Doron¹, Juan C Caicedo¹

¹Broad Institute of MIT and Harvard, United States.

Current Opinion in Chemical Biology

|May 23, 2021

Summary

This summary is machine-generated.

Deep learning advances cell biology by enabling sophisticated visual cell phenotyping. This technology analyzes complex cellular images to identify, profile, and predict phenotypes, answering key biological questions.

Keywords:

Cell phenotyping Deep learning Image analysis Phenotypic screening

More Related Videos

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons

Published on: July 7, 2023

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

Published on: August 22, 2025

Related Experiment Videos

Last Updated: Nov 4, 2025

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Published on: October 4, 2024

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons

Published on: July 7, 2023

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

Published on: August 22, 2025

Area of Science:

Cell Biology
Computational Biology
Biotechnology

Background:

Cellular phenotype arises from complex molecular interactions, resulting in unique morphological signatures.
Visual cell phenotyping quantifies observable cellular traits in images.
Recent technological advances have dramatically increased the scale, resolution, and throughput of cell imaging.

Purpose of the Study:

To review applications of deep learning in visual cell phenotyping.
To highlight how deep learning addresses challenges in high-throughput cell biology.
To demonstrate deep learning's role in answering biological questions through phenotype analysis.

Main Methods:

Leveraging advances in electronic, optical, and chemical imaging technologies.
Applying deep learning algorithms for image analysis and interpretation.
Utilizing computational tools for high-throughput analysis of cellular phenotypes.

Main Results:

Deep learning powers the recognition, profiling, and prediction of visual phenotypes.
Computational solutions are provided for analyzing complex and large-scale imaging assays.
New avenues for innovation in cell biology are opened by these advancements.

Conclusions:

Deep learning is transforming visual cell phenotyping.
It enables the elucidation of previously unexplored cellular phenotypes.
Deep learning is crucial for addressing complex biological questions in modern cell biology.