Nutritional Phenotype Database (dbnp)

Nutritional Phenotype Database (dbNP) integrates genetics, transcriptomics, proteomics, biomarkers, metabolomics, functional assays, genotype, participant phenotypes, dietary intake, and study design metadata to enable analysis of diet–genotype–phenotype relationships in nutrition research.

Key Features:

• Integration of Multi-Omics Data: Stores and links pre-processed omics data including genetics, transcriptomics, proteomics, biomarkers, metabolomics, and functional assays for integrated analysis.
• Comprehensive Study Descriptions: Links study design metadata with participant phenotypes, genotype, and dietary intake to contextualize omics measurements.
• Modular Database Architecture: Implements a modular, federated data storage architecture that supports integration and interrogation of datasets across studies and research groups.
• Standardized Protocols and Annotations: Embeds standard procedures, data management protocols, and comprehensive annotations to ensure consistent representation of datasets.

Scientific Applications:

• Diet–genotype–phenotype interaction analysis: Enables investigation of relationships among diet, genotype, and phenotype using integrated multi-omics and metadata.
• Investigation of bioactive food compounds: Supports studies on how bioactive compounds in foods affect molecular and physiological processes using omics and biomarker data.
• Personalized nutrition and disease research: Facilitates development of personalized nutrition strategies and studies of diet in disease prevention and management by linking molecular profiles with dietary intake and phenotypes.

Methodology:

Stores pre-processed omics data; links study design metadata with participant phenotypes, genotype, and dietary intake; uses a modular, federated database architecture; and applies standardized data management protocols and annotations.