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Related Concept Videos

Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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Diversity in Cell Signaling Responses

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Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Understanding cellular function and disease with comparative pathway analysis.

Melissa J Davis1, Mark A Ragan1

  • 1The University of Queensland, Institute for Molecular Bioscience, ARC Centre of Excellence in Bioinformatics, St Lucia, Queensland 4072, Australia.

Genome Medicine
|July 30, 2013
PubMed
Summary
This summary is machine-generated.

Pathway analysis helps interpret high-throughput experiments but faces comparison challenges. Pathprinting offers a novel cross-platform, cross-species method for analyzing pathway expression signatures, improving cancer gene discovery.

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A Web Tool for Generating High Quality Machine-readable Biological Pathways
08:01

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

Published on: February 8, 2017

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Genomics

Background:

  • Interpreting high-throughput experimental results relies on pathway analysis.
  • Comparing pathway expression signatures across different platforms and species is a significant challenge.
  • Existing methods lack robustness for cross-platform and cross-species comparisons.

Purpose of the Study:

  • To introduce Pathprinting, a novel computational approach for comparative pathway analysis.
  • To enable cross-platform and cross-species analysis of pathway expression signatures.
  • To demonstrate the utility of Pathprinting in identifying biologically relevant patterns and prognostic markers.

Main Methods:

  • Pathprinting calculates pathway-level statistics from gene expression data.
  • The method leverages a large dataset of nearly 180,000 microarrays from the Gene Expression Omnibus (GEO).
  • Comparative analysis is performed across diverse platforms and species (human and mouse).

Main Results:

  • Pathprinting accurately retrieves phenotypically similar samples.
  • The method successfully identifies sets of human and mouse genes that are prognostic in cancer.
  • Demonstrates robust cross-platform and cross-species comparability of pathway expression signatures.

Conclusions:

  • Pathprinting provides a robust solution for cross-platform and cross-species pathway analysis.
  • This approach enhances the interpretation of functional implications from high-throughput experiments.
  • Pathprinting facilitates the discovery of conserved and prognostic gene sets in cancer across species.