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What is Gene Expression?

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Studying and modelling dynamic biological processes using time-series gene expression data.

Ziv Bar-Joseph1, Anthony Gitter, Itamar Simon

  • 1Lane Center for Computational Biology and Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA. zivbj@cs.cmu.edu

Nature Reviews. Genetics
|July 19, 2012
PubMed
Summary
This summary is machine-generated.

Researchers analyze dynamic biological processes using time-series gene expression data. This review covers patterns, computational analysis, and modeling of cellular systems for deeper biological insights.

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Last Updated: May 20, 2026

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Area of Science:

  • Molecular Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Biological processes are inherently dynamic and require multi-time point monitoring.
  • Time-series gene expression data is a primary source for understanding these dynamics.
  • Analyzing gene expression over time reveals gene activation, rates of change, and causal relationships.

Purpose of the Study:

  • To review fundamental patterns in time-series gene expression data.
  • To explain how these patterns form biological expression programs.
  • To discuss computational methods for analyzing, visualizing, and integrating this data for dynamic system modeling.

Main Methods:

  • Review of existing literature on time-series gene expression analysis.
  • Discussion of pattern recognition in temporal gene activity.
  • Exploration of computational tools for data integration and visualization.

Main Results:

  • Identification of basic patterns in time-series gene expression.
  • Understanding the composition of gene expression programs.
  • Framework for computational analysis and modeling of dynamic biological systems.

Conclusions:

  • Time-series gene expression data is crucial for deciphering dynamic biological processes.
  • Computational approaches are essential for extracting meaningful models from complex temporal data.
  • This review provides a foundation for analyzing and interpreting dynamic biological systems.