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Overview of the protein-protein interaction annotation extraction task of BioCreative II
TLDR
The BioCreative II PPI task is the first attempt to compare the performance of text-mining tools specific for each of the basic steps of the PPI extraction pipeline, and challenges identified range from problems in full-text format conversion of articles to difficulties in detecting interactor protein pairs and then linking them to their database records. Expand
CHEMDNER: The drugs and chemical names extraction challenge
TLDR
This task allowed a comparative assessment of the performance of various methodologies using a carefully prepared collection of manually labeled text prepared by specially trained chemists as Gold Standard data, and expected that the tools and resources resulting from this effort will have an impact in future developments of chemical text mining applications. Expand
Overview of the BioCreative VI chemical-protein interaction Track
TLDR
The BioCreative VI ChemProt track represents the first attempt to promote the development of systems for extracting chemical-protein interactions (CPIs), of relevance for precision medicine as well as for drug discovery and basic biomedical research. Expand
Automatic De-identification of Medical Texts in Spanish: the MEDDOCAN Track, Corpus, Guidelines, Methods and Evaluation of Results
TLDR
This paper summarizes the settings, data and results of the first shared track on anonymization of medical documents in Spanish, the MEDDOCAN (Medical Document Anonymization) track, which relied on a carefully constructed synthetic corpus of clinical case documents following annotation guidelines for sensitive data based on the analysis of the EU General Data Protection Regulation. Expand
Evaluation of BioCreAtIvE assessment of task 2
TLDR
Concepts provided by GO are currently the most extended set of terms used for annotating gene products, thus they were explored to assess how effectively text mining tools are able to extract those annotations automatically. Expand
Linking genes to literature: text mining, information extraction, and retrieval applications for biology
TLDR
This review presents a general introduction to the main characteristics and applications of currently available text-mining systems for life sciences in terms of the type of biological information demands being addressed; the level of information granularity of both user queries and results; and the features and methods commonly exploited by these applications. Expand
An Overview of BioCreative II.5
TLDR
The BioCreative II.5 challenge evaluated automatic annotations from 15 text mining teams based on a gold standard created by reconciling annotations from curators, authors, and automated systems, and ensemble systems improved performance for the interacting protein task. Expand
Overview of the CHEMDNER patents task
A considerable effort has been made to extract biological and chemical entities, as well as their relationships, from the scientific literature, either manually through traditional literatureExpand
Text-mining and information-retrieval services for molecular biology
TLDR
A range of text-mining applications have been developed recently that will improve access to knowledge for biologists and database annotators. Expand
Overview of the BioCreative III Workshop
TLDR
It is concluded that the best performing systems for GN, P PI-ACT and PPI-IMT in realistic settings are not sufficient for fully automatic use and the importance of interactive systems is presented. Expand
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