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NLM-Chem, a new resource for chemical entity recognition in PubMed full text literature.
Islamaj, Rezarta; Leaman, Robert; Kim, Sun; Kwon, Dongseop; Wei, Chih-Hsuan; Comeau, Donald C; Peng, Yifan; Cissel, David; Coss, Cathleen; Fisher, Carol; Guzman, Rob; Kochar, Preeti Gokal; Koppel, Stella; Trinh, Dorothy; Sekiya, Keiko; Ward, Janice; Whitman, Deborah; Schmidt, Susan; Lu, Zhiyong.
Afiliação
  • Islamaj R; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Leaman R; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Kim S; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Kwon D; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Wei CH; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Comeau DC; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Peng Y; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Cissel D; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Coss C; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Fisher C; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Guzman R; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Kochar PG; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Koppel S; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Trinh D; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Sekiya K; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Ward J; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Whitman D; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Schmidt S; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • Lu Z; National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA. Zhiyong.Lu@nih.gov.
Sci Data ; 8(1): 91, 2021 03 25.
Article em En | MEDLINE | ID: mdl-33767203
ABSTRACT
Automatically identifying chemical and drug names in scientific publications advances information access for this important class of entities in a variety of biomedical disciplines by enabling improved retrieval and linkage to related concepts. While current methods for tagging chemical entities were developed for the article title and abstract, their performance in the full article text is substantially lower. However, the full text frequently contains more detailed chemical information, such as the properties of chemical compounds, their biological effects and interactions with diseases, genes and other chemicals. We therefore present the NLM-Chem corpus, a full-text resource to support the development and evaluation of automated chemical entity taggers. The NLM-Chem corpus consists of 150 full-text articles, doubly annotated by ten expert NLM indexers, with ~5000 unique chemical name annotations, mapped to ~2000 MeSH identifiers. We also describe a substantially improved chemical entity tagger, with automated annotations for all of PubMed and PMC freely accessible through the PubTator web-based interface and API. The NLM-Chem corpus is freely available.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Compostos Orgânicos / Software / Preparações Farmacêuticas / Mineração de Dados / Terminologia como Assunto Idioma: En Revista: Sci Data Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Compostos Orgânicos / Software / Preparações Farmacêuticas / Mineração de Dados / Terminologia como Assunto Idioma: En Revista: Sci Data Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos