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We developed HRGRN, a Graph search-empowered integrative database of Arabidopsis signaling transduction, metabolism, and gene regulation networks, with an emphasis on hormone signaling and gene regulatory pathways. The database is designed to host and discover interactions among genes, proteins, compounds, and small RNAs through integrative analysis of heterogeneous interactions. The HRGRN utilizes the highly scalable, robust native graph database, Neo4j, to hosts and integrates biological interactions between proteins, compound and protein, transcription factor and target gene, small RNA and target gene, transporter and substrate, enzyme and substrate/product. We also added gene pair with similar expression pattern, gene family/complex and member as well as modified protein and original type into HRGRN as interactions. These interactions were either validated by experiments or predicted by computational approach. The hormone-associated interactions are highlighted to facilitate the exploration to hormone biosynthesis, secretion, signaling and regulation related functions in Arabidopsis.






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  • (2019), "HRGRN,"

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