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

Imaging Biological Samples with Optical Microscopy

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...

You might also read

Related Articles

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

Sort by

Same author

Photoactivatable BODIPY Dyes Conjugated to Self-Labeling Protein Tags.

ACS applied bio materials·2026

Same author

Case Report: When catatonia-like symptoms are not catatonia: Guillain-Barré syndrome in a patient with schizophrenia.

Frontiers in psychiatry·2026

Same author

Cognitive function and depressive symptoms in major depressive disorder: a smartphone-based study of outpatients from a sleep-disorders clinic in China.

Frontiers in psychiatry·2026

Same author

Solvatochromic BODIPYs with Polarity-Independent Absorption for Functional Super-resolution Imaging of Live Cell Membranes.

Chemical & biomedical imaging·2026

Same author

Effects of a phone-based, CBT-I-centered digital intervention on sleep and depressive symptoms in real-world clinical settings.

BMC psychiatry·2026

Same author

Spectroscopic DNA-PAINT for simultaneous multiplexed super-resolution microscopy.

bioRxiv : the preprint server for biology·2026

Same journal

Complex Indel Detection: A Simulation-Based Framework and Parsing with FreeBayes.

bioRxiv : the preprint server for biology·2026

Same journal

Emulating the gingival-tooth interface during bacterial, fungal, and viral infection in a microphysiological model of the human oral cavity.

bioRxiv : the preprint server for biology·2026

Same journal

Local SNP-explained methylation variation reveals genetically anchored and exposure-associated methylation architecture in the human brain.

bioRxiv : the preprint server for biology·2026

Same journal

Perinatal Semaglutide Treatment Improves Maternal Health and Mitigates Offspring Metabolic Dysfunction in a Mouse Model of Maternal Obesity.

bioRxiv : the preprint server for biology·2026

Same journal

Pervasive cryptic selection in the human noncoding genome.

bioRxiv : the preprint server for biology·2026

Same journal

Secreted ORF8 reprograms macrophages to enhance SARS-CoV-2 infection of lung epithelial cells.

bioRxiv : the preprint server for biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 5, 2026

4D Imaging of Protein Aggregation in Live Cells

4D Imaging of Protein Aggregation in Live Cells

Published on: April 5, 2013

SIMBA: an agentic AI platform for single-molecule multidimensional imaging.

Hongjing Mao^1,2, Harsh Mauny³, Obblivignes KanchanadeviVenkataraman^1,3

¹Molecular Analytics and Photonics (MAP) Lab, North Carolina State University, Raleigh, NC 27606, USA.

Biorxiv : the Preprint Server for Biology

|May 4, 2026

Summary

This summary is machine-generated.

We developed SIMBA, an AI platform for multi-dimensional bioimaging. It unifies single-molecule localization, spectral analysis, and deep learning denoising, simplifying complex microscopy data analysis for researchers.

More Related Videos

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

Published on: May 30, 2016

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

Related Experiment Videos

Last Updated: May 5, 2026

4D Imaging of Protein Aggregation in Live Cells

4D Imaging of Protein Aggregation in Live Cells

Published on: April 5, 2013

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

Published on: May 30, 2016

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

Area of Science:

Biophysics
Microscopy
Computational Biology

Background:

Super-resolution fluorescence microscopy advances enable functional, multi-dimensional imaging.
Challenges include fragmented analysis, complex tuning, and limited computational integration.

Purpose of the Study:

Introduce SIMBA, an AI-driven platform for unified single-molecule multi-dimensional bioimaging.
Simplify and enhance the analysis of complex microscopy data.

Main Methods:

Developed SIMBA, an agentic AI platform integrating single-molecule localization, spectral processing, and deep learning denoising.
Utilized large language model agents for user intent interpretation and automated pipeline orchestration.
Implemented supervised learning for spectral analysis and denoising.

Main Results:

SIMBA supports standard single-molecule localization workflows.
Enabled functional mapping of nanoscale heterogeneity via spectral analysis.
Demonstrated effective denoising using supervised learning methods.

Conclusions:

SIMBA offers a new paradigm for intelligent microscopy analysis.
Lowers adoption barriers for multi-dimensional imaging.
Enables scalable, reproducible, and adaptive analysis of complex bioimaging datasets.