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Updated: Jul 16, 2026

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

Published on: February 8, 2017

Enabling high-throughput data management for systems biology: the Bioinformatics Resource Manager.

Anuj R Shah1, Mudita Singhal, Kyle R Klicker

  • 1Biomolecular Systems Initiative, Pacific Northwest National Laboratory, Richland, WA, USA. anuj.shah@pnl.gov

Bioinformatics (Oxford, England)
|February 28, 2007
PubMed
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The Bioinformatics Resource Manager (BRM) is a free software tool simplifying complex biological data analysis. It integrates diverse datasets and connects to visualization tools, aiding researchers in data management and retrieval.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Data Science

Background:

  • Biological data analysis involves managing and integrating diverse datasets from various platforms.
  • Current tools may not adequately address the complexities of merging microarray and proteomic data.
  • Seamless integration with public functional annotation and interaction data is often challenging.

Purpose of the Study:

  • To introduce the Bioinformatics Resource Manager (BRM) as a comprehensive software environment.
  • To simplify data management, retrieval, and integration for biological analyses.
  • To enhance the usability of complex biological data for researchers.

Main Methods:

  • BRM is developed using Java and open-source technologies.
  • It provides capabilities for data merging, integration with public databases, and reformatting for analysis tools.

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An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus

Published on: November 30, 2014

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  • Designed in collaboration with biologists to address practical needs.

    • Main Results:

    • BRM offers streamlined data management and retrieval.
    • Facilitates integration of user data with public functional and interaction datasets.
    • Enables connectivity to visual analytic tools through data reformatting.

    Conclusions:

    • BRM simplifies complex, multi-platform data analysis tasks for biologists.
    • The software enhances data integration and accessibility for research.
    • BRM is freely available, promoting wider adoption in the scientific community.