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Protein Networks

Protein Networks

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.
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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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Genome Annotation and Assembly

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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

Updated: Nov 30, 2025

A Web Tool for Generating High Quality Machine-readable Biological Pathways

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

A Systems Bioinformatics Approach to Interconnect Biological Pathways.

George Minadakis¹, George M Spyrou²

¹Department of Bioinformatics, The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus. georgem@cing.ac.cy.

Methods in Molecular Biology (Clifton, N.J.)

|November 12, 2020

Summary

PathwayConnector links biological pathways to reveal crucial connections for understanding complex diseases. This web tool aids in personalized medicine by analyzing gene and protein networks across multiple organisms and databases.

Keywords:

Clusters of pathways Pathway analysis Pathway networks

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

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Area of Science:

Systems biology
Bioinformatics
Genomics

Background:

Complex biological processes rely on interconnected gene, protein, and metabolite pathways.
Classical functional analysis often overlooks pathway interconnectivity, hindering a complete understanding.
Understanding these networks is crucial for deciphering molecular mechanisms of complex diseases.

Purpose of the Study:

To introduce and detail the methodology of PathwayConnector, a web tool for constructing pathway-to-pathway networks.
To highlight the tool's capability in identifying missing pathways essential for disease mechanism elucidation.
To demonstrate its utility in analyzing novel biological data within a broader network context.

Main Methods:

Utilizes an expanded pathway reference network integrating data from KEGG and REACTOME.
Supports analysis of data from 19 different organisms, accommodating both large-scale (omics) and small-scale experimental results.
Describes the pipeline for rapidly relating pathways across different organisms.

Main Results:

PathwayConnector facilitates the construction of complementary pathway networks.
Identifies previously overlooked pathways critical for understanding disease.
Enables the projection and analysis of novel genes, proteins, and pathways.

Conclusions:

Pathway networks and subnetworks generated by PathwayConnector are vital for disease individualization.
The tool supports a more precise and personalized approach to disease management and treatment.
PathwayConnector enhances the understanding of complex biological processes and molecular mechanisms.