RaMP-DB 2.0: a renovated knowledgebase for deriving biological and chemical insight from metabolites, proteins, and genes

John Braisted, Andrew Patt, Cole Tindall, Timothy Shiels, Jorge Neyra, Kyle Spencer, Tara Eicher, Ewy Mathe

Abstract:

Motivation: Functional interpretation of high-throughput metabolomic and transcriptomic results is a crucial step in
generating insight from experimental data. However, pathway and functional information for genes and metabolites
are distributed among many siloed resources, limiting the scope of analyses that rely on a single knowledge source.
Results: RaMP-DB 2.0 is a web interface, relational database, API and R package designed for straightforward and
comprehensive functional interpretation of metabolomic and multi-omic data. RaMP-DB 2.0 has been upgraded with
an expanded breadth and depth of functional and chemical annotations (ClassyFire, LIPID MAPS, SMILES, InChIs,
etc.), with new data types related to metabolites and lipids incorporated. To streamline entity resolution across multiple source databases, we have implemented a new semi-automated process, thereby lessening the burden of harmonization and supporting more frequent updates. The associated RaMP-DB 2.0 R package now supports queries
on pathways, common reactions (e.g. metabolite-enzyme relationship), chemical functional ontologies, chemical
classes and chemical structures, as well as enrichment analyses on pathways (multi-omic) and chemical classes.
Lastly, the RaMP-DB web interface has been completely redesigned using the Angular framework.