BiomeNet
BiomeNet constructs and analyzes functional interaction networks across sequenced genomes to enable functional annotation and prediction of gene functions, supporting projects such as the Earth BioGenome Project.
Key Features:
- Extensive Network Database: 95 scored networks comprising over 8 million co-functional links spanning 5 animal, 6 plant, 5 bacterial, and 2 fungal species.
- Orthologous Protein Link Transfer: Transfers co-functional links between orthologous proteins from source networks to target species, enabling automatic construction of gene networks with quality comparable to existing databases.
- Predictive and Analytical Capabilities: Enables assembly of first-in-species gene networks predictive of diverse biological processes, extraction of function-specific subnetworks, and network-based gene prioritization.
- Facilitation of Functional Annotation: Uses network biology to place gene function predictions in the context of collaborative gene interactions for genome annotation.
Scientific Applications:
- Functional annotation: Supports functional annotation and molecular network analyses for newly sequenced genomes to elucidate gene functions and pathways.
- Biodiversity genomics: Supports large-scale efforts such as the Earth BioGenome Project by transferring functional links across taxa.
- Research applications: Enables predictive network analyses relevant to genetics, evolutionary biology, and ecology.
Methodology:
Transferring co-functional links from 95 scored, validated source networks between orthologous proteins to construct target-species gene networks.
Topics
Details
- Added:
- 1/9/2020
- Last Updated:
- 11/24/2024
Operations
Publications
Kim E, Bae D, Yang S, Ko G, Lee S, Lee B, Lee I. BiomeNet: a database for construction and analysis of functional interaction networks for any species with a sequenced genome. Bioinformatics. 2019;36(5):1584-1589. doi:10.1093/bioinformatics/btz776. PMID:31599923. PMCID:PMC7703761.
PMID: 31599923
PMCID: PMC7703761
Funding: - MSIT: NRF-2018M3C9A5064704, NRF-2018M3C9A5064709, NRF-2018R1A5A2025079, NRF-2019M3A9B6065192