Evolutionary hypernetwork classifiers for protein-proteininteraction sentence filtering
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Syntactic dependency based heuristics for biological event extraction
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
A metalearning approach to processing the scope of negation
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
Learning the scope of negation in biomedical texts
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Evaluating a meta-knowledge annotation scheme for bio-events
NeSp-NLP '10 Proceedings of the Workshop on Negation and Speculation in Natural Language Processing
Modality and negation: An introduction to the special issue
Computational Linguistics
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Motivation: Negative information about protein–protein interactions—from uncertainty about the occurrence of an interaction to knowledge that it did not occur—is often of great use to biologists and could lead to important discoveries. Yet, to our knowledge, no proposals focusing on extracting such information have been proposed in the text mining literature. Results: In this work, we present an analysis of the types of negative information that is reported, and a heuristic-based system using a full dependency parser to extract such information. We performed a preliminary evaluation study that shows encouraging results of our system. Finally, we have obtained an initial corpus of negative protein–protein interactions as basis for the construction of larger ones. Availability: The corpus is available by request from the authors. Contact:osanch@essex.ac.uk or poesio@essex.ac.uk