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Distributed retrieval engine for the development of cloud-deployed biological databases.

David Bouzaglo1, Israel Chasida1, Elishai Ezra Tsur1

  • 1Neuro-biomorphic Engineering Lab, Faculty of Engineering, Jerusalem College of Technology, Jerusalem, Israel.

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Summary
This summary is machine-generated.

This study introduces a framework for cloud-based biological databases, enhancing data maintenance and accessibility. It addresses challenges in integrating diverse biological data for improved research.

Keywords:
Cloud-based databasesFederated databasesMongoDBSpecialized databases

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Area of Science:

  • Biomedical Informatics
  • Database Management
  • Cloud Computing

Background:

  • Specialized biomedical databases face challenges in maintenance, accessibility, and performance.
  • Integrating diverse biological data requires expertise in cloud computing and unified data models.

Purpose of the Study:

  • To propose a framework for developing cloud-based specialized biological databases.
  • To enable efficient data retrieval and exploration across heterogeneous biological data formats.

Main Methods:

  • Developed a framework using Java and MongoDB.
  • Implemented a distributed biodata retrieval system.
  • Utilized open libraries such as BSON, jsoup, Apache Commons, and w3c.dom for syntactic analysis.

Main Results:

  • The framework facilitates the integration of cloud resources with federated data retrieval.
  • It provides an integrated approach for exploring diverse biological data.
  • The system supports interfacing with various data formats.

Conclusions:

  • The proposed framework offers a viable solution for building robust and accessible cloud-based biological databases.
  • It simplifies the management and exploration of complex biological datasets.
  • The framework is available under a Creative Commons agreement.