We believe that more elaborate approaches for detecting these ignored but highly confident functional assignments (e.g. methods based on natural-language processing of full text journal articles [ 54]) would extract considerably more annotations than our simple keyword-based PubMed search (see Methods for details).
The State-of-the-art technologies such as GOPubmed use simple keyword-based techniques for retrieving abstracts from the PubMed and linking them to the Gene Ontology (GO).
For convenience, the proposed DPDs based on simple LUT, LILUT and QILUT are called as LUT-based, LILUT-based, and QILUT-based, respectively.
Instead, it is based on simple mathematics.
This interface, called Entrez (http://www.ncbi.nlm.nih.gov/sites/gquery/) [ 25], provides a simple entry point for searching biomedical information based on keyword-based searches including terms from selected lexical resources such as the MeSH thesaurus and links among related data.
Endogenous links between segments, within the collection, were established based on a simple keyword comparison heuristics.
In order to check the generalizability of the resulting classifiers, we have in the experiments compared the results to a baseline, implemented as a rule-based algorithm based on the keywords used to select the appropriate tweets.
Based on keyword extraction methods, keywords reflecting certain concepts can be extracted from the content of Web documents.
Figure 10 depicts an example where two hints are automatically generated via simple queries (constructed based on the keywords "Amazon" and "SpecJEnterprise" found in the question body) to the CAMEL repository.
Most regression-based sensitivity analyses published are based on relatively simple linear models fitted by OLS Regression [ 37].
