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

Engineering Ultrathin Bismuth Nanosheets With Active Facet for Highly Efficient CO<sub>2</sub> Electroreduction to Formate.

ChemSusChem·2026

Same author

ZILA-SRM: a probabilistic framework with zero-inflated latent models for robust strain reconstruction from metagenomes.

Microbiology spectrum·2026

Same author

Depressive symptom trajectories around incident hip fracture in older adults: an event-centered matched analysis from the Health and Retirement Study.

Maturitas·2026

Same author

Cognitive trajectories before and after geriatric hip fracture: a matched longitudinal analysis of the Health and Retirement Study, 1996-2016.

BMC geriatrics·2026

Same author

Molecular mechanisms of KMT2C alterations in gastrointestinal cancers: enhancer network destabilization, lineage plasticity, and clinical translation.

Frontiers in immunology·2026

Same author

Discovery of novel 20S-protopanaxadiol derivatives in alleviating sepsis-associated liver injury by modulating p65/p50 activity.

European journal of medicinal chemistry·2026

Search research articles

Related Experiment Video

Updated: Aug 29, 2025

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

Published on: May 22, 2017

INSISTC: Incorporating network structure information for single-cell type classification.

Hansi Zheng¹, Saidi Wang¹, Xiaoman Li²

¹Department of Computer Science, University of Central Florida, Orlando, FL 32816, USA.

|September 8, 2022

Summary

We developed INSISTC, a new computational method for single-cell type classification that integrates gene regulatory network structures. This approach enhances understanding of cell-specific gene regulation and improves cell classification accuracy.

Keywords:

Gene regulatory Gene regulatory network Single-cell type classification

More Related Videos

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Published on: August 1, 2022

Related Experiment Videos

Last Updated: Aug 29, 2025

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

Published on: May 22, 2017

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Published on: August 1, 2022

Area of Science:

Computational Biology
Genomics
Systems Biology

Background:

Single-cell RNA sequencing (scRNA-seq) enables gene regulation analysis at single-cell resolution, crucial for understanding cell heterogeneity and function.
Accurate cell type and state identification relies on understanding cell-type-specific gene regulation.
Current computational methods face challenges in determining gene regulatory relationships and incorporating gene regulatory network structures for cell classification.

Purpose of the Study:

To develop a novel computational method, INSISTC, for single-cell type classification.
To integrate gene regulatory network structure information into the classification process.
To identify cell-type-specific gene regulatory mechanisms concurrently with cell classification.

Main Methods:

Developed INSISTC, a computational method that incorporates gene regulatory network structure information.
Applied INSISTC to single-cell data for classification and gene regulatory mechanism discovery.
Compared INSISTC's performance against alternative methods.

Main Results:

INSISTC accurately classifies cell types.
INSISTC identifies cell-type-specific gene regulatory mechanisms.
INSISTC demonstrates complementary performance for gene regulation interpretation compared to existing methods.

Conclusions:

INSISTC effectively integrates gene regulatory network information for improved single-cell type classification.
The method provides insights into molecular mechanisms specific to individual cells.
INSISTC offers a valuable tool for advancing single-cell analysis and understanding gene regulation.