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

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...

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

Protein Networks

Protein Networks

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...

Master Transcription Regulators

Master Transcription Regulators

Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...

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...

You might also read

Related Articles

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

Sort by

Same author

Comprehensive analysis of the RBP regulome reveals functional modules and drug candidates in liver cancer.

Scientific reports·2026

Same author

GeneSNAKE: a Python package for simulation of gene regulatory networks and perturbation-induced expression data.

Bioinformatics advances·2026

Same author

scVIP: personalized modeling of single-cell transcriptomes for developmental and disease phenotypes.

bioRxiv : the preprint server for biology·2026

Same author

<i>MapMyCells:</i> High-performance mapping of unlabeled cell-by-gene data to reference brain taxonomies.

bioRxiv : the preprint server for biology·2026

Same author

Enhancer dynamics and cellular architecture in the human spinal cord.

Neuron·2026

Same author

Cell cycle-driven transcriptome maturation confers multilineage competence to cardiopharyngeal progenitors.

The EMBO journal·2025

Search research articles

Related Experiment Video

Updated: Mar 2, 2026

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

GeneSPIDER - gene regulatory network inference benchmarking with controlled network and data properties.

Andreas Tjärnberg¹, Daniel C Morgan, Matthew Studham

¹Stockholm Bioinformatics Center, Science for Life Laboratory, Sweden. torbjorn.nordling@nordlinglab.org erik.sonnhammer@scilifelab.se.

Molecular Biosystems

|May 10, 2017

Summary

GeneSPIDER is a new Matlab package for evaluating biological network inference accuracy. It enables data-driven benchmarking by simulating networks and data to understand algorithm performance.

More Related Videos

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

Related Experiment Videos

Last Updated: Mar 2, 2026

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

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

Area of Science:

Computational Biology
Systems Biology
Bioinformatics

Background:

Assessing the accuracy of biological network inference methods is a critical, yet unanswered, question.
Existing benchmarking methods often lack the flexibility to account for specific biological data properties.

Purpose of the Study:

To introduce GeneSPIDER, a Matlab package for data-driven benchmarking of network inference algorithms.
To enable independent control of network and data properties for robust algorithm evaluation.
To facilitate a deeper understanding of how network and data characteristics influence inference accuracy.

Main Methods:

GeneSPIDER extracts salient properties from experimental data.
It generates simulated networks and data that closely match these properties.
The package includes pipelines for experiment design, bootstrapping, and performance evaluation.

Main Results:

GeneSPIDER facilitates data-driven algorithm selection and estimation of inference accuracy.
It supports multifaceted benchmarking by controlling network and data properties.
The tool aids in understanding the impact of signal-to-noise ratio (SNR) and other factors on performance.

Conclusions:

GeneSPIDER advances network inference benchmarking beyond simple performance metrics.
It provides a framework for understanding the interplay between data properties and algorithm accuracy.
The package promotes more informed selection and development of network inference tools.