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Prediction of protein complexes from proteinprotein interaction (PPI) networks is crucial to unraveling the principles of cellular organization. Most existing approaches only exploit high-throughput experimental PPI data to predict protein complexes. In this paper, we integrate the multiple biomedical resources for protein complex prediction by constructing attributed PPI networks, which include high-throughput...
Protein complexes can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of protein complexes detection...
This paper focuses on setting up a question-answering oriented biomedical domain, and it applies several different approaches to the different processing phases. Firstly, it uses shallow parser to identify the types of questions and extract the keywords, and the keywords are expanded with UMLS for the purpose of improving the recall. Secondly, passage retrieval is performed with the expanded keywords...
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