DOI: 10.1101/451625Oct 24, 2018Paper

PathMe: Merging and exploring mechanistic pathway knowledge

BioRxiv : the Preprint Server for Biology
Daniel Domingo-FernandezMartin Hofmann-Apitius

Abstract

Background The complexity of representing biological systems is compounded by an ever-expanding body of knowledge emerging from multi-omics experiments. A number of pathway databases have facilitated pathway-centric approaches that assist in the interpretation of molecular signatures yielded by these experiments. However, the lack of interoperability between pathway databases has hindered the ability to harmonize these resources and to exploit their consolidated knowledge. Such a unification of pathway knowledge is imperative in enhancing the comprehension and modeling of biological abstractions. Results Here, we present PathMe, a Python package that transforms pathway knowledge from three major pathway databases into a unified abstraction using Biological Expression Language as the pivotal, integrative schema. PathMe is complemented by a novel web application (freely available at <https://pathme.scai.fraunhofer.de/>) which allows users to comprehensively explore pathway crosstalks and compare areas of consensus and discrepancies. Conclusions This work has harmonized three major pathway databases and transformed them into a unified schema in order to gain a holistic picture of pathway knowledge. We demonstrate the utility of ...Continue Reading

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