The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

作者：Martin Krallinger, Miguél Vázquez, Florian Leitner, David Salgado, Andrew Chatr‐aryamontri, Andrew G. Winter, Livia Perfetto, Leonardo Briganti, Luana Licata, Marta Iannuccelli, Luisa Castagnoli, Gianni Cesareni, Mike Tyers, Gerold Schneider, Fabio Rinaldi, Robert Leaman, Graciela Gonzalez‐Hernandez, Sérgio Matos, Sun Kim, W. John Wilbur, Luis Mateus Rocha, Hagit Shatkay, Ashish V. Tendulkar, Shashank Agarwal, Feifan Liu, Xinglong Wang, Rafał Rak, Keith Noto, Charles Elkan, Zhiyong Lu, Rezarta Islamaj, Jean−Fred Fontaine, Miguel Angel Andrade-Navarro, Alfonso Valencia · 发表于：BMC Bioinformatics · 年份：2011 · DOI：10.1186/1471-2105-12-s8-s3 · 被引用次数：185 · 研究领域：Biomedical Text Mining and Ontologies、Bioinformatics and Genomic Networks、Topic Modeling

BACKGROUND: Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them. RESULTS: A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team w...