A semantic layer for unifying and exploring biomedical document curation results

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Abstract

Tackling the ever-growing amount of specialized literature in the life sciences domain is a paramount challenge. Various scientific workflows depend on using domain knowledge from resources that summarize, in structured form, validated information extracted from scientific publications. Manual curation of these data is a demanding task, and latest strategies use computerized solutions to aid in the analysis, extraction and storage of relevant concepts and their respective attributes and relationships. The outcome of these complex document curation workflows provides valuable insights into the overwhelming amount of biomedical information being produced. Yet, the majority of automated and interactive annotation tools are not open, limiting access to knowledge and reducing the potential scope of the manually curated information. In this manuscript, we propose an interoperable semantic layer to unify document curation results and enable their proper exploration through multiple interfaces geared towards bioinformatics developers and general life sciences researchers. This enables a unique scenario where results from computational annotation tools are harmonized and further integrated into rich semantic knowledge bases, providing a solid foundation for discovering knowledge.

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APA

Sernadela, P., Lopes, P., Campos, D., Matos, S., & Oliveira, J. L. (2015). A semantic layer for unifying and exploring biomedical document curation results. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9043, pp. 8–17). Springer Verlag. https://doi.org/10.1007/978-3-319-16483-0_2

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