Can the vector space model be used to identify biological entity activities?
The VSM extended with a transitive closure approach provides a good way to identify biological interactions from textual collections. Specifically for the context of literature-based discovery, the extended VSM contributes to identify and rank relevant new interactions even if these interactions occur in only a few documents in the collection. Consequently, we have developed an efficient method for extracting and restricting the best potential results to consider as new advances in life sciences, even when indications of these results are not easily observed from a mass of documents.
We conclude that two distinct cellular responses to radiation, p53-independent apoptosis and p53-dependent G1-arrest, influence radiobiological parameters that characterize the radiation response of glioblastoma cells. Further understanding of the molecular basis of GM radiation resistance will lead to improvement in existing therapeutic modalities and to the development of novel treatment approaches.