arXiv Open Access 2019

An Information Extraction and Knowledge Graph Platform for Accelerating Biochemical Discoveries

Matteo Manica Christoph Auer Valery Weber Federico Zipoli Michele Dolfi +7 lainnya
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Abstrak

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.

Topik & Kata Kunci

Penulis (12)

M

Matteo Manica

C

Christoph Auer

V

Valery Weber

F

Federico Zipoli

M

Michele Dolfi

P

Peter Staar

T

Teodoro Laino

C

Costas Bekas

A

Akihiro Fujita

H

Hiroki Toda

S

Shuichi Hirose

Y

Yasumitsu Orii

Format Sitasi

Manica, M., Auer, C., Weber, V., Zipoli, F., Dolfi, M., Staar, P. et al. (2019). An Information Extraction and Knowledge Graph Platform for Accelerating Biochemical Discoveries. https://arxiv.org/abs/1907.08400

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2019
Bahasa
en
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arXiv
Akses
Open Access ✓