Building resource-efficient community databases using open-source software
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View abstract on PubMed
Summary
This summary is machine-generated.Developing integrated crop databases is crucial for utilizing big data in plant breeding. This study presents five community databases built using open-source tools to support genomics and genetics research.
Area Of Science
- Plant genomics and breeding
- Bioinformatics and data management
- Agricultural science
Background
- Big data in nonmodel crop species is rapidly increasing.
- Existing crop databases face insufficient and intermittent funding, leading to underutilization of valuable data.
- There is a critical need for efficient methods to build and maintain community databases for crop research.
Purpose Of The Study
- To address the need for integrated database resources for crop genomics, genetics, and breeding research.
- To describe the system and methods for constructing, curating, and analyzing data in community crop databases.
- To provide access to data and tools through five established crop databases.
Main Methods
- Development of five crop databases over ten years using an open-source platform and software.
- Implementation of data curation and analysis protocols.
- Integration of diverse datasets relevant to crop research.
Main Results
- Successful establishment of five community crop databases: Genome Database for Rosaceae (GDR), Genome Database for Vaccinium (GDV), Citrus Genome Database (CGD), Pulse Crop Database (PCD), and CottonGen.
- These databases provide curated data and analytical tools for researchers.
- The open-source approach facilitates sustainable database development.
Conclusions
- The developed crop databases offer essential integrated resources for the genomics, genetics, and breeding communities.
- Utilizing open-source technology provides an efficient and sustainable model for building community databases.
- These databases will enhance the utilization of big data in crop improvement efforts.
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