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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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Related Experiment Video

Updated: Jun 18, 2026

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

A method of biological pathway similarity search using high performance computing.

Keyuan Jiang1, Yingmeng Huang, Joseph Robertson

  • 1Department of Computer Information Technology and Graphics, Purdue University Calumet, Hammond, IN 46323, USA. jiang@calumet.purdue.edu

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
Summary

A new method compares biological pathways to understand their functions and evolution. This computational approach uses a scoring system for similarity searches in pathway databases.

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Last Updated: Jun 18, 2026

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A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
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Published on: July 1, 2020

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Biological pathways are fundamental to cellular functions.
  • Comparing pathways aids in understanding novel pathways, evolutionary relationships, and identifying missing components.
  • Existing methods may lack efficiency for large-scale pathway analysis.

Purpose of the Study:

  • To develop and implement a novel method for pairwise comparison and similarity searching of biological pathways.
  • To enable elucidation of biological pathway functions, evolutionary traits, and identification of missing elements.
  • To create a scalable solution for analyzing biological pathway data.

Main Methods:

  • Pathway comparison based on structural and compositional differences.
  • Development of a scoring mechanism for ranking pathway similarities.
  • Implementation of the method within the Condor high-performance computing environment for efficient processing.
  • Utilizing XML format for representing biological pathways.

Main Results:

  • A functional method for pairwise biological pathway comparison has been established.
  • A similarity search capability using a scoring mechanism is available for pathway repositories.
  • The implementation leverages high-performance computing for enhanced performance.

Conclusions:

  • The developed method provides a robust approach for biological pathway analysis.
  • This computational tool facilitates deeper insights into pathway functions and evolution.
  • High-performance computing integration ensures scalability and efficiency for large biological datasets.