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Automated gene data integration with Databio
Robert W Reid1,2, Jacob W Ferrier1, Jeremy J Jay3,4
1Department of Bioinformatics and Genomics, College of Computing and Informatics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA.
BMC Research Notes
|April 3, 2020
Summary
Databio automates data analysis and integration for life sciences, simplifying complex -omics data. This tool aids researchers by streamlining data manipulation and linking resources without requiring specialized bioinformatics expertise.
Area of Science:
- Life Sciences Research
- Translational Medicine
- -omics Studies
Background:
- Data analysis and interpretation are major cost factors in -omics studies.
- Integrating data across multi-disciplinary projects is challenging.
- Scientists struggle to keep up with research across multiple fields.
Purpose of the Study:
- To develop a computational tool for automated data parsing and identifier detection.
- To streamline data manipulation and integration in life sciences.
- To enable data linkage without specialized bioinformatics knowledge.
Main Methods:
- Development of the Databio tool (https://datab.io/).
- Utilizes fast real-time data structures and a large identifier data warehouse (137 million identifiers).
- Employs automated heuristics for data provenance description.
Main Results:
- Databio provides a point-and-click interface for data manipulation and integration.
- Automates common tasks, including identifier detection.
- Facilitates data linkage and understanding for researchers.
Conclusions:
- Databio simplifies complex data analysis and integration in life sciences and translational medicine.
- Reduces the need for specialized bioinformatics training.
- Enhances data discoverability and linkage for multi-disciplinary research.
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