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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,...
Introduction to Differential Equations01:20

Introduction to Differential Equations

A differential equation is a mathematical expression that establishes a relationship between a function and its derivatives. These equations are fundamental in modeling dynamic systems across various fields of science and engineering. The order of a differential equation is defined by the highest order derivative present in the equation. A first-order differential equation includes only the first derivative, while a second-order differential equation includes up to the second derivative of the...
Circuit Terminology01:14

Circuit Terminology

An electrical network is a system composed of interconnected elements, such as resistors, capacitors, inductors, and voltage or current sources. Unlike a circuit, an electrical network does not necessarily form a closed path. In other words, while all circuits can be considered networks due to their interconnected nature, not every network qualifies as a circuit.
A circuit, on the other hand, is also an interconnected system of electrical elements but must contain one or more closed paths.
Signal and System01:26

Signal and System

A signal x(t) is a set of data or a time function representing a variable of interest. Signals typically convey information about a phenomenon, such as atmospheric temperature, humidity, human voice, television images, a dog's bark, or birdsongs. More generally, a signal can be a function of more than one independent variable. For instance, images depend on horizontal and vertical positions and can be regarded as two-dimensional signals. However, this text will focus on one-dimensional signals...
Classification of Systems-II01:31

Classification of Systems-II

Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,

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Updated: May 29, 2026

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

Published on: October 19, 2021

Introduction to network analysis in systems biology.

Avi Ma'ayan1

  • 1Department of Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine, New York, NY 10029, USA. avi.maayan@mssm.edu

Science Signaling
|September 16, 2011
PubMed
Summary

This resource introduces graph theory and network analysis for systems biology. Learn to model intracellular networks, analyze network properties, and predict gene functions using biological data.

Area of Science:

  • Systems Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Biological systems are complex networks.
  • Understanding these networks is crucial for biomedical research.
  • Traditional analysis methods may not capture network dynamics.

Purpose of the Study:

  • To provide educational materials on applying graph theory and network analysis in systems biology.
  • To introduce methods for constructing and analyzing biological networks.
  • To demonstrate predictive applications of network analysis in biomedical modeling.

Main Methods:

  • Lecture notes, slides, and problem sets covering three core topics.
  • Introduction to intracellular network types and construction methods.
  • Explanation of network analysis concepts, topological measures, and models.

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Last Updated: May 29, 2026

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

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

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  • Discussion of gene list analysis and prediction using prior knowledge networks.

    • Main Results:

    • Comprehensive teaching materials are available for "Systems Biology: Biomedical Modeling."
    • The lectures cover network construction, analysis, and predictive modeling.
    • The resource facilitates learning advanced computational techniques in biology.

    Conclusions:

    • Graph theory and network analysis are powerful tools for systems biology.
    • These methods enable deeper understanding and prediction of biological processes.
    • The provided materials serve as a valuable educational resource for the field.