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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...

Cis-regulatory Sequences

Cis-regulatory Sequences

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...

Constitutive and Regulated Gene Expression

Constitutive and Regulated Gene Expression

Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...

Neural Regulation

Neural Regulation

Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.

Regulation of Expression Occurs at Multiple Steps

Regulation of Expression Occurs at Multiple Steps

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Related Experiment Video

Updated: Dec 15, 2025

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

Gene regulatory network inference from sparsely sampled noisy data.

Atte Aalto¹, Lauri Viitasaari², Pauliina Ilmonen³

¹Luxembourg Centre for Systems Biomedicine, University of Luxembourg; 6 avenue du Swing, 4367, Belvaux, Luxembourg.

Nature Communications

|July 15, 2020

Summary

This summary is machine-generated.

This study introduces BINGO, a novel method for gene regulatory network inference. BINGO effectively addresses limitations in biological time-series data, outperforming existing methods for deciphering life's complex mechanisms.

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Area of Science:

Systems Biology
Genomics
Bioinformatics

Background:

Biological complexity is governed by gene regulatory networks (GRNs).
Understanding GRNs is crucial for disease treatment and biological mechanism discovery.
Inferring GRNs is challenging due to limited, noisy, low-frequency, and small-sample time-series data.

Purpose of the Study:

To develop a robust method for gene regulatory network inference.
To address data limitations including noise, low sampling frequency, and small sample sizes.
To improve the accuracy and accessibility of GRN inference.

Main Methods:

Developed BINGO, a novel nonparametric method for GRN inference.
Utilized statistical sampling of continuous gene expression profiles.
Benchmarked BINGO using diverse real and simulated time-series gene expression data.

Main Results:

BINGO consistently outperformed state-of-the-art methods in GRN inference.
Demonstrated superior performance across various simulated and real biological datasets.
Highlighted the effectiveness of the nonparametric approach with statistical sampling.

Conclusions:

BINGO offers a significant advancement in gene regulatory network inference.
The method's superior performance and ease of use democratize GRN analysis for researchers.
Facilitates a deeper understanding of the complex mechanisms of life and disease.