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Biomedical relation extraction: from binary to complex.
Zhou, Deyu; Zhong, Dayou; He, Yulan.
Afiliação
  • Zhou D; School of Computer Science and Engineering, Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China.
  • Zhong D; School of Computer Science and Engineering, Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China.
  • He Y; School of Engineering and Applied Science, Aston University, Birmingham B4 7ET, UK.
Comput Math Methods Med ; 2014: 298473, 2014.
Article em En | MEDLINE | ID: mdl-25214883
ABSTRACT
Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. Early biomedical relation extraction tasks focused on capturing binary relations, such as protein-protein interactions, which are crucial for virtually every process in a living cell. Information about these interactions provides the foundations for new therapeutic approaches. In recent years, more interests have been shifted to the extraction of complex relations such as biomolecular events. While complex relations go beyond binary relations and involve more than two arguments, they might also take another relation as an argument. In the paper, we conduct a thorough survey on the research in biomedical relation extraction. We first present a general framework for biomedical relation extraction and then discuss the approaches proposed for binary and complex relation extraction with focus on the latter since it is a much more difficult task compared to binary relation extraction. Finally, we discuss challenges that we are facing with complex relation extraction and outline possible solutions and future directions.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia / Mineração de Dados / Medicina Limite: Humans Idioma: En Revista: Comput Math Methods Med Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2014 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia / Mineração de Dados / Medicina Limite: Humans Idioma: En Revista: Comput Math Methods Med Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2014 Tipo de documento: Article País de afiliação: China