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

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

You might also read

Related Articles

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

Sort by

Same author

Integration of Transcriptomics With Interpretable Artificial Intelligence for Identifying Molecular Signatures of Physiological Stress in Sleep Deprivation.

Journal of cellular and molecular medicine·2026

Same author

Noninvasive Risk Stratification Based on Renal Tubular Injury Phenotypes: A Deep Learning Study for Predicting Vesicoureteral Reflux in Children.

Journal of cellular and molecular medicine·2026

Same author

E-SegNet: E-Shaped Structure Networks for Accurate 2D and 3D Medical Image Segmentation.

Research (Washington, D.C.)·2025

Same author

A Multi-Task Self-Supervised Strategy for Predicting Molecular Properties and FGFR1 Inhibitors.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025

Same author

Dear-PSM: A deep learning-based peptide search engine enables full database search for proteomics.

Smart medicine·2024

Same author

STORM image denoising and information extraction.

Biomedical physics & engineering express·2024

Search research articles

Related Experiment Video

Updated: May 7, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

The network structural entropy for single-cell RNA sequencing data during skin aging.

Zhilong Liu¹, Hai Lin², Xiang Li¹

¹Department of Physics, Xiamen University, No. 422, Siming South Road, Xiamen, Fujian, 361005, China.

Briefings in Bioinformatics

|January 5, 2025

Summary

This summary is machine-generated.

Aging increases gene network complexity, with varying effects across cell types. Analyzing network structural entropy offers insights into cellular aging mechanisms and functions.

Keywords:

aging cellular heterogeneity gene regulatory networks network structural entropy single-cell RNA sequencing

More Related Videos

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis

Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis

Published on: May 16, 2020

Related Experiment Videos

Last Updated: May 7, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis

Characterization of In Vitro Differentiation of Human Primary Keratinocytes by RNA-Seq Analysis

Published on: May 16, 2020

Area of Science:

Genomics
Computational Biology
Aging Research

Background:

Aging is a complex biological process with poorly understood molecular mechanisms.
Existing research has not fully elucidated the heterogeneity of aging at the cellular level.

Purpose of the Study:

To analyze aging-related gene networks using single-cell RNA sequencing data.
To quantify the complexity of gene networks during aging using network structural entropy.

Main Methods:

Constructed a gene correlation network from over 15,000 single-cell RNA sequencing cells.
Integrated gene expression data into network edge weights.
Utilized a random walk model to rank gene importance and introduced network structural entropy.

Main Results:

Overall network structural entropy increased in aged cells compared to young cells.
Network entropy changes varied significantly across different cell subtypes, showing increases, decreases, or no change.
Cellular heterogeneity in aging is linked to functional differences and key network reconfigurations.

Conclusions:

Network structural entropy analysis provides novel insights into the molecular mechanisms of aging.
The study highlights the heterogeneity of cellular aging and its impact on gene networks.
Findings offer new evidence for understanding age-related changes in cell function.