KnetMiner

KnetMiner integrates genome-scale knowledge graphs, scientific literature, and biological datasets to support evidence-based gene discovery and analysis of complex traits across sequenced species.

Key Features:

• Knowledge Network Integration: Integrates genome-scale knowledge graphs to link genes, traits, pathways, phenotypes, and literature evidence.
• Data Search and Genomic Queries: Supports keyword searches, gene-list queries, and region-specific genomic investigations for targeted data retrieval.
• Gene Ranking and Enrichment Analysis: Provides gene ranking based on relevance to traits or conditions and performs gene set enrichment analysis to identify significant pathways.
• Hypothesis Generation and Evidence Synthesis: Synthesizes information from scientific literature and public datasets to generate evidence-based hypotheses, including applications such as linking grain color and pre-harvest sprouting in wheat (Triticum aestivum) and identifying candidate genes for petal size QTLs in Arabidopsis thaliana.
• Cross-Species Application: Applies the same knowledge-network-based analyses to any species with a sequenced genome for comparative and translational investigations.

Scientific Applications:

• Evidence-based gene discovery: Identifies candidate genes by integrating heterogeneous evidence from knowledge graphs and literature.
• Complex trait analysis in plants and crops: Dissects genetic links underlying traits such as grain color and pre-harvest sprouting in Triticum aestivum and petal size QTLs in Arabidopsis thaliana.
• Pathway and functional interpretation: Uses gene ranking and enrichment results to prioritize biological pathways and functional hypotheses for experimental follow-up.
• Cross-species comparative analysis: Facilitates transfer of knowledge and candidate gene hypotheses across species with sequenced genomes.

Methodology:

Integrates genome-scale knowledge graphs with scientific literature and biological datasets; supports keyword, gene-list, and region queries; performs gene ranking and gene set enrichment analysis and synthesizes evidence from public datasets for hypothesis generation.