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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

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-protein Interfaces

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...

Interactions Between Signaling Pathways

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...

Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Related Experiment Video

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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

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Published on: October 19, 2021

Combining many interaction networks to predict gene function and analyze gene lists.

Sara Mostafavi¹, Quaid Morris

¹Department of Computer Science, Stanford University, Stanford, CA, USA.

|May 17, 2012

Summary

Interaction networks help predict gene and protein function. A gene-recommender system, like GeneMANIA, analyzes these networks to identify gene roles and functions.

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Last Updated: May 22, 2026

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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

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Published on: June 17, 2012

Area of Science:

Bioinformatics
Computational Biology
Systems Biology

Background:

Gene and protein function prediction is crucial for understanding biological systems.
Interaction networks offer a powerful data source for functional inference.

Purpose of the Study:

To review the application of interaction networks for gene and protein function prediction.
To introduce the concept of a gene-recommender system.
To highlight the GeneMANIA system as a specific example.

Main Methods:

Utilizing large collections of gene and protein interaction networks.
Developing and applying "gene-recommender systems" for automated function prediction.
Focusing on the GeneMANIA system and its unique algorithms.

Main Results:

Interaction networks, used alone or in combination, provide insights into gene and protein function.
Gene-recommender systems can predict gene/protein function based on query lists.
GeneMANIA demonstrates unique features and algorithms for network analysis.

Conclusions:

Automated analysis of interaction networks is effective for predicting gene and protein functions.
Gene-recommender systems represent a valuable approach for functional genomics.
GeneMANIA offers advanced capabilities for exploring gene and protein functions through interaction networks.