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Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
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,...
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...
Hedgehog Signaling Pathway02:33

Hedgehog Signaling Pathway

The Hedgehog gene (Hh) was first discovered due to its control of the growth of disorganized, hair-like bristles phenotype in Drosophila, much like hedgehog spines. Hh plays a crucial role in the development of organs and the maintenance of homeostasis in both invertebrates and vertebrates. However, while Drosophila has only one Hh protein, mammals have multiple functional Hedgehog proteins - Sonic (Shh), Desert (Dhh), and Indian Hedgehog (Ihh). All of these homologous proteins have adapted to...
IP3/DAG Signaling Pathway01:11

IP3/DAG Signaling Pathway

Membrane lipids such as phosphatidylinositol (PI) are precursors for several membrane-bound and soluble second messengers. Specific kinases phosphorylate PI and produce phosphorylated inositol phospholipids. One such inositol phospholipids are the  phosphatidylinositol-4,5 bisphosphate [PI(4,5)P2], present in the inner half of the lipid bilayer. Upon ligand binding, GPCR stimulates Gq proteins to turn on phospholipase Cꞵ. Activated phospholipase Cꞵ cleaves PI(4,5)P2 and produces two-second...
RNA Interference01:23

RNA Interference

RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
This process occurs naturally in cells, often through the activity of genomically-encoded microRNAs. Researchers can take advantage of this mechanism by introducing synthetic RNAs to deactivate specific genes for research or therapeutic purposes. For example, RNAi could be used...

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Related Experiment Video

Updated: Jun 22, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Reconstructing signaling pathways from RNAi data using probabilistic Boolean threshold networks.

Lars Kaderali1, Eva Dazert, Ulf Zeuge

  • 1Viroquant Research Group Modeling, University of Heidelberg, Bioquant BQ26, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany. lars.kaderali@bioquant.uni-heidelberg.de

Bioinformatics (Oxford, England)
|June 23, 2009
PubMed
Summary
This summary is machine-generated.

This study presents a Bayesian network approach to reconstruct gene signaling pathways from incomplete RNA interference (RNAi) knockdown data. The method effectively infers network topology and parameters, even with missing observations, aiding in pathway elucidation.

Related Experiment Videos

Last Updated: Jun 22, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Area of Science:

  • Systems Biology
  • Computational Biology
  • Genomics

Background:

  • Reconstructing gene signaling pathways from gene knockdown data is a novel research area.
  • RNA interference (RNAi) screening technology enables this but pathway placement is challenging, especially with incomplete data.
  • Inferring networks from partial observations is a significant hurdle in systems biology.

Purpose of the Study:

  • To develop a computational method for inferring gene signaling pathway topologies from incomplete gene knockdown data.
  • To address the challenge of underdetermined network parameters in pathway reconstruction.
  • To enable the design of additional experiments based on inferred network properties.

Main Methods:

  • Utilized Bayesian networks with probabilistic Boolean threshold functions for pathway topology inference.
  • Employed a Bayesian learning approach to integrate prior information and handle underdetermined parameters.
  • Integrated out missing observations and used approximate likelihood evaluation for larger networks.
  • Applied mode hopping Markov chain Monte Carlo for posterior distribution evaluation.

Main Results:

  • Successfully inferred pathway topologies and network parameters from incomplete gene knockdown data.
  • Demonstrated the method's capability to handle missing observations effectively.
  • Applied the approach to RNAi data from the Jak/Stat pathway in human hepatoma cells, providing inference results.

Conclusions:

  • The developed Bayesian network approach provides a robust framework for reconstructing gene signaling pathways from incomplete knockdown data.
  • The method's ability to integrate prior knowledge and handle missing data makes it valuable for systems biology research.
  • The inferred network distributions can guide future experimental designs for pathway validation.