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Related Concept Videos

Protein Networks02:26

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 Networks02:26

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,...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
Synthetic Biology02:55

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...

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Related Experiment Video

Updated: Jun 28, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

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

Published on: December 7, 2021

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external

Maryam Shahdoust1, Rosa Aghdam2, Mehdi Sadeghi2,3

  • 1School of Biological Sciences, Institute For Research In Fundamental Sciences (IPM), 19395-5746, Tehran, Iran. m.shahdoost@ipm.ir.

BMC Bioinformatics
|June 26, 2026
PubMed
Summary

SimMapNet improves gene regulatory network (GRN) reconstruction by integrating Gene Ontology (GO) similarities. This novel Bayesian approach enhances accuracy, especially with limited sample sizes, outperforming existing methods.

Keywords:
Bayesian inferenceGaussian graphical modelGene ontology similaritiesGene regulatory networks

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Systems biology

Background:

  • Gene regulatory network (GRN) reconstruction is vital for understanding gene interactions.
  • Existing methods face challenges, particularly with limited sample sizes.

Purpose of the Study:

  • To develop a novel Bayesian framework, SimMapNet, for GRN reconstruction.
  • To integrate Gene Ontology (GO) similarities into GRN inference.
  • To improve the accuracy and efficiency of GRN construction.

Main Methods:

  • SimMapNet utilizes a Bayesian framework to estimate the precision matrix for undirected GRN inference.
  • It incorporates GO similarities (Molecular Function, Biological Process, Cellular Component) via a kernel function.
  • The method employs a Gaussian Graphical Model for network estimation.

Main Results:

  • SimMapNet demonstrated superior performance (F1-score) compared to GLASSO, GENIE3, and KBOOST on E. coli and Drosophila melanogaster datasets.
  • The algorithm exhibits low time complexity, suitable for large-scale network construction.
  • Simulations confirmed SimMapNet's effectiveness in limited sample size scenarios.

Conclusions:

  • SimMapNet offers a principled and effective method for GRN reconstruction by leveraging biological prior knowledge from GO.
  • The framework provides enhanced accuracy and efficiency, particularly beneficial for datasets with few samples.
  • This approach advances computational biology by improving our ability to infer gene regulatory relationships.