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Annotation guidelines used for the annotations of gene and protein-related objects of the CHEMDNER, ChemProt and DrugProt corpora.
Please cite if you use any DrugProt resource:
Antonio Miranda-Escalada, Farrokh Mehryary, Jouni Luoma, Darryl Estrada-Zavala, Luis Gasco, Sampo Pyysalo, Alfonso Valencia, Martin Krallinger, Overview of DrugProt task at BioCreative VII: data and methods for large-scale text mining and knowledge graph generation of heterogenous chemical\u2013protein relations, Database, Volume 2023, 2023, baad080
@article{miranda2023overview, title={Overview of DrugProt task at BioCreative VII: data and methods for large-scale text mining and knowledge graph generation of heterogenous chemical--protein relations}, author={Miranda-Escalada, Antonio and Mehryary, Farrokh and Luoma, Jouni and Estrada-Zavala, Darryl and Gasco, Luis and Pyysalo, Sampo and Valencia, Alfonso and Krallinger, Martin}, journal={Database}, volume={2023}, pages={baad080}, year={2023}, publisher={Oxford University Press UK} }
Miranda, Antonio, et al. \"Overview of DrugProt BioCreative VII track: quality evaluation and large scale text mining of drug-gene/protein relations.\" Proceedings of the seventh BioCreative challenge evaluation workshop. 2021.
@inproceedings{miranda2021overview, title={Overview of DrugProt BioCreative VII track: quality evaluation and large scale text mining of drug-gene/protein relations}, author={Miranda, Antonio and Mehryary, Farrokh and Luoma, Jouni and Pyysalo, Sampo and Valencia, Alfonso and Krallinger, Martin}, booktitle={Proceedings of the seventh BioCreative challenge evaluation workshop}, year={2021} }
Introduction
The annotation guidelines have been refined after iterative cycles of annotations of sample documents. It also incorporated suggestions made by curators as well as observations of annotation inconsistencies encountered when comparing results from different human curators.
In brief, the annotated GPROs include genes, gene products
(proteins, RNA), DNA/protein sequence elements and protein families, domains and complexes. The aim of the iterative manual annotation cycles was to improve the quality and consistency of the guidelines, in order to make them more intuitive and easier to follow.
Please, cite:
@article{perez2016markyt, title={The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge}, author={P{\\'e}rez-P{\\'e}rez, Martin and P{\\'e}rez-Rodr{\\'\\i}guez, Gael and Rabal, Obdulia and Vazquez, Miguel and Oyarzabal, Julen and Fdez-Riverola, Florentino and Valencia, Alfonso and Krallinger, Martin and Louren{\\c{c}}o, An{\\'a}lia}, journal={Database}, volume={2016}, year={2016}, publisher={Oxford Academic}}
Related Resources:
A considerable amount of medically relevant information is hidden in large unstructured heterogeneous data collections, such as the medical literature, medicinal patents, electronic health records or specialized web-content (health blogs, patient forums or information generated by scientific and medical societies). To process more efficiently medical big data there is a growing interest in exploiting natural language processing and text mining approaches, in particularly deep learning and artificial intelligence-based strategies.
\n\nA considerable amount of medically relevant information is hidden in large unstructured heterogeneous data collections, such as the medical literature, medicinal patents, electronic health records or specialized web-content (health blogs, patient forums or information generated by scientific and medical societies). To process more efficiently medical big data there is a growing interest in exploiting natural language processing and text mining approaches, in particularly deep learning and artificial intelligence-based strategies.
\n\nThe aim of the Plan de Impulso de las Tecnologías del Lenguaje (Plan TL), the Spanish national Plan for the Advancement of Language Technology, is to promote the development of resources of critical importance for processing textual data in Spanish as well as Catalan, Basque and Galician. The Health and biomedical domain constitute one of the flagship topics of the Spanish Plan TL.
\n\nTo promote the development of health-related language technology applications, the Plan TL is both developing and identifying resources of key relevance including individual components/libraries, terminological resources, annotated corpora and annotation guidelines, as well as document collections and language models.
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