KGen: a knowledge graph generator from biomedical scientific literature.

Journal: BMC medical informatics and decision making
Published Date: Dec 14, 2020

Abstract

BACKGROUND: Knowledge is often produced from data generated in scientific investigations. An ever-growing number of scientific studies in several domains result into a massive amount of data, from which obtaining new knowledge requires computational help. For example, Alzheimer's Disease, a life-threatening degenerative disease that is not yet curable. As the scientific community strives to better understand it and find a cure, great amounts of data have been generated, and new knowledge can be produced. A proper representation of such knowledge brings great benefits to researchers, to the scientific community, and consequently, to society.

Authors

  • Anderson Rossanez
    Institute of Computing, University of Campinas, Campinas, SP, Brazil. anderson.rossanez@ic.unicamp.br.
  • Julio Cesar Dos Reis
    Faculty of Campo Limpo Paulista, Rua Guatemala, 167, 13231-230 Campo Limpo Paulista, SP, Brazil; Luxembourg Institute of Science and Technology, 29 Avenue John F. Kennedy, L-1855 Luxembourg, Luxembourg. Electronic address: juliocesardosreis@gmail.com.
  • Ricardo da Silva Torres
    Department of ICT and Natural Sciences, Faculty of Information Technology and Electrical Engineering, NTNU - Norwegian University of Science and Technology, Ålesund, Norway.
  • Hélène de Ribaupierre
    School of Computer Science and Informatics, Cardiff University, Cardiff, UK.

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