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Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
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attract: A method for identifying core pathways that define cellular phenotypes.

Jessica C Mar1, Nicholas A Matigian, John Quackenbush

  • 1Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America. jess@jimmy.harvard.edu

Plos One
|October 25, 2011
PubMed
Summary
This summary is machine-generated.

ATTRACT is a knowledge-driven method that identifies gene sets distinguishing cell phenotypes. It finds patterns in pathways, creating meta-genes and synexpression groups for biological system analysis.

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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Identifying gene sets that differentiate cell phenotypes is crucial for understanding biological systems.
  • Existing methods may not fully capture complex gene expression patterns within pathways.

Purpose of the Study:

  • To present ATTRACT, a novel knowledge-driven analytical approach.
  • To enable the identification and annotation of gene sets that effectively discriminate between cell phenotypes.

Main Methods:

  • ATTRACT analyzes biological pathways to find distinguishing patterns.
  • It decomposes pathways into representative meta-genes.
  • Generates synexpression groups of highly correlated genes from transcriptome data.

Main Results:

  • ATTRACT successfully identifies gene sets that discriminate between cell phenotypes.
  • The approach generates meta-genes and synexpression groups.
  • Demonstrates applicability across diverse biological systems.

Conclusions:

  • ATTRACT provides a robust method for analyzing gene expression data.
  • It facilitates the discovery of biologically relevant gene sets.
  • The tool is accessible as a Bioconductor package and within MeV software.