QxDB: a generic database to support mathematical modelling in biology

Area of Science:

• Computational Biology
• Bioinformatics
• Data Management

Background:

• Centralized access to quantitative and structural data is crucial for developing mathematical models.
• Existing databases often lack detailed quality assessments of experimental results.
• Researchers need reliable data for both mathematical modeling and experimental validation.

Purpose of the Study:

• To introduce QxDB, a web-based database package for quantitative and structural information.
• To provide a platform that supports the development of mathematical models and serves the broader research community.
• To enhance data usability through expert-curated quality evaluations.

Main Methods:

• Developed QxDB using PHP and MySQL for broad compatibility and adaptability.
• Integrated expert commentary on experimental techniques, validity, and conditions for each data record.
• Designed QxDB with customizable descriptor tables for adaptation to various research domains.

Main Results:

• QxDB offers a centralized repository for quantitative and structural research data.
• Expert annotations provide critical context for evaluating data quality and appropriateness.
• The database structure allows for customization, demonstrated by applications in oncology and cell/tissue mechanics.

Conclusions:

• QxDB facilitates the development of mathematical models by providing curated, quality-assessed data.
• Its flexible design and expert commentary enhance its utility for both modelers and experimentalists.
• QxDB serves as a valuable, adaptable resource for diverse scientific research fields.