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Related Concept Videos

Cell Specific Gene Expression01:58

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
RNA-seq03:21

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 microarray-based...
Experimental RNAi02:15

Experimental RNAi

RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...

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Related Experiment Video

Updated: May 9, 2026

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
06:24

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

DeepCE: a deep learning framework for correlation-enhanced gene regulatory network inference in single-cell RNA

Qianqian Wu1, Xingmiao Dai1, Shiyi Lou1

  • 1School of Mathematics, Hefei University of Technology, Hefei, Anhui 230009, China.

Bioinformatics Advances
|February 20, 2026
PubMed
Summary
This summary is machine-generated.

We developed DeepCE, a deep learning framework to infer gene regulatory networks (GRNs). DeepCE enhances accuracy and reliability in understanding gene expression dynamics and cellular heterogeneity.

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Last Updated: May 9, 2026

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
06:24

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Published on: July 29, 2022

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells
06:02

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

Published on: October 28, 2025

Area of Science:

  • Computational Biology
  • Genomics
  • Bioinformatics

Background:

  • Single-cell RNA sequencing (scRNA-seq) reveals gene expression dynamics and cellular heterogeneity.
  • Deep learning (DL) shows promise for inferring genetic regulation but struggles with complex mechanisms.
  • New algorithms are needed to improve the effectiveness and reliability of gene regulatory network (GRN) inference.

Purpose of the Study:

  • To introduce DeepCE, a novel DL framework designed for correlation-enhanced GRN inference.
  • To improve the accuracy and robustness of GRN inference by integrating advanced DL techniques.

Main Methods:

  • DeepCE integrates bidirectional gated recurrent units (GRUs) with convolutional neural networks (CNNs).
  • Bidirectional GRUs capture dynamic temporal dependencies in gene expression data.
  • CNNs analyze local spatial patterns within scRNA-seq data to uncover complex gene-gene interactions.

Main Results:

  • DeepCE enhances the extraction of dynamic gene regulation.
  • The framework smooths noisy gene expression data, extracts time-lagged regulatory signals, and filters spurious correlations.
  • Experiments on mouse and human datasets show DeepCE outperforms existing methods, achieving superior AUROC and AUPR scores.

Conclusions:

  • DeepCE provides a powerful and reliable framework for high-quality GRN inference.
  • The proposed method advances the understanding of gene regulatory mechanisms from single-cell data.
  • DeepCE offers improved accuracy and robustness compared to current state-of-the-art approaches.