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KDD 2019Knowledge graphsWorkshop

An Information Extraction and Knowledge Graph Platform for Accelerating Biochemical Discoveries

A scalable document ingestion system builds a biochemistry knowledge graph integrating databases and PDFs to accelerate biochemical discovery.

Matteo Manica, Christoph Auer, Valéry Weber, Federico Zipoli, Michele Dolfi, Peter Staar, Teodoro Laino, Costas Bekas, Akihiro Fujita, Toda, Hiroki, Shuichi Hirose, Yasumitsu Orii

Published Jul 19, 20198 citationsarXiv ↗

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Abstract

Information extraction and data mining in biochemical literature is a daunting task that demands resource-intensive computation and appropriate means to scale knowledge ingestion. Being able to leverage this immense source of technical information helps to drastically reduce costs and time to solution in multiple application fields from food safety to pharmaceutics. We present a scalable document ingestion system that integrates data from databases and publications (in PDF format) in a biochemistry knowledge graph (BCKG). The BCKG is a comprehensive source of knowledge that can be queried to retrieve known biochemical facts and to generate novel insights. After describing the knowledge ingestion framework, we showcase an application of our system in the field of carbohydrate enzymes. The BCKG represents a way to scale knowledge ingestion and automatically exploit prior knowledge to accelerate discovery in biochemical sciences.