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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

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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...

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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...

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Related Experiment Video

Updated: Apr 18, 2026

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

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

Published on: October 19, 2021

Reputation-based collaborative network biology.

, Jean Binder¹, Stephanie Boue

¹Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing

|January 17, 2015

Summary

This summary is machine-generated.

The Bionet platform leveraged collective intelligence to enhance biological networks for lung biology. Standardized knowledge representation is key for successful collaborative network biology.

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Area of Science:

Systems Biology
Computational Biology
Bioinformatics

Background:

Verification of complex biological networks is crucial for understanding disease mechanisms.
Previous network models of lung biology required enhancement and validation.
Collaborative approaches can harness collective intelligence for biological data analysis.

Purpose of the Study:

To pilot a reputation-based collaborative network biology platform, Bionet.
To verify and enhance existing biological networks using crowd-sourced knowledge.
To assess the viability of collaborative platforms in systems biology.

Main Methods:

Development of the Bionet platform incorporating a reputation system.
Utilizing crowd-sourced input for network verification and enhancement.
Employing a standardized biological knowledge representation language (BEL).

Main Results:

Bionet successfully captured a more comprehensive view of lung biology networks.
The platform demonstrated the effectiveness of collective intelligence in network biology.
A standardized biological knowledge representation language proved critical for platform success.

Conclusions:

The Bionet pilot confirmed the viability of collaborative network biology platforms.
Standardized knowledge representation is essential for successful collaborative systems biology.
Future enhancements for scalability will benefit academic and industry researchers.