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Combinatorial Gene Control

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...

Cis-regulatory Sequences

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...

Regulation of Expression at Multiple Steps

Regulation of Expression at Multiple Steps

The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...

Regulation of Expression Occurs at Multiple Steps

Regulation of Expression Occurs at Multiple Steps

Regulation of Expression Occurs at Multiple Steps

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...

Lineage Commitment

Lineage Commitment

Commitment is the process whereby stem cells:

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Related Experiment Video

Updated: Jan 8, 2026

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Published on: June 21, 2016

Identifying Combinatorial Regulatory Genes for Cell Fate Decision via Reparameterizable Subset Explanations.

Junhao Liu¹, Pengpeng Zhang¹, Martin Renqiang Min²

¹University of California, Irvine, Department of Computer Science, Irvine, California, USA.

KDD : Proceedings. International Conference on Knowledge Discovery & Data Mining

|December 22, 2025

Summary

MetaVelo identifies key gene sets driving cell fate transitions using a novel framework. This approach enhances understanding of developmental biology and disease by revealing complex gene interactions.

Keywords:

AI for Science Regulatory Gene Identification Single-Cell Data

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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

Related Experiment Videos

Last Updated: Jan 8, 2026

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Published on: June 21, 2016

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

Area of Science:

Developmental Biology
Computational Biology
Genomics

Background:

Cell fate decisions are complex, involving intricate gene interactions.
Disruptions in these processes can cause developmental issues and diseases.
Existing methods struggle to model these combinatorial gene interactions effectively.

Purpose of the Study:

Introduce MetaVelo, a framework for identifying key regulatory gene sets in cell fate transitions.
Overcome limitations of traditional methods in capturing combinatorial gene effects.
Provide a scalable tool for analyzing single-cell RNA sequencing data.

Main Methods:

Model cell fate transitions as a black-box function.
Utilize a differentiable neural ordinary differential equation (ODE) surrogate for optimization.
Reparameterize the problem as a controllable data generation process.

Main Results:

MetaVelo outperforms 12 baseline methods in predicting developmental trajectories.
Successfully identifies combinatorial regulatory gene sets influencing cell fate.
Distinguishes between independent and synergistic regulatory genes.

Conclusions:

MetaVelo offers a superior framework for understanding cell fate dynamics.
Provides novel insights into gene interactions critical for development and disease.
Enables advancements in developmental biology and therapeutic applications using single-cell data.