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Related Concept Videos

Principles of Disease Surveillance01:26

Principles of Disease Surveillance

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Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
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Related Experiment Video

Updated: Apr 5, 2026

IR-TEx: An Open Source Data Integration Tool for Big Data Transcriptomics Designed for the Malaria Vector Anopheles gambiae
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A Framework for Global Collaborative Data Management for Malaria Research.

Juan B Gutierrez, Omar S Harb, Jie Zheng

    The American Journal of Tropical Medicine and Hygiene
    |August 12, 2015
    PubMed
    Summary
    This summary is machine-generated.

    The International Centers of Excellence for Malaria Research (ICEMR) developed data management principles and a web information system to handle complex, large-scale malaria research data, enabling collaborative research and data sharing.

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    Area of Science:

    • Malariology
    • Bioinformatics
    • Data Science

    Background:

    • Malaria research generates heterogeneous, large-scale, and multi-scaled data.
    • Federated and global data operations present significant challenges for collaborative research.
    • Diverse data applications require sophisticated management strategies.

    Purpose of the Study:

    • To present foundational data management principles for the International Centers of Excellence for Malaria Research (ICEMR) Program.
    • To describe the logistics of the data life cycle within the ICEMR Program.
    • To introduce a pilot centralized web information system in PlasmoDB for data querying.

    Main Methods:

    • Developing foundational data management principles.
    • Addressing data life cycle logistics.
    • Creating a pilot centralized web information system using PlasmoDB.

    Main Results:

    • Established data management principles for the ICEMR Program.
    • Detailed logistics for various data life cycle aspects.
    • Developed a functional pilot web information system for querying ICEMR data.

    Conclusions:

    • The proposed data management paradigm is effective for large, multifaceted research projects.
    • The system and principles are adaptable to other complex data management contexts.
    • Facilitates collaborative research through improved data accessibility and management.