1 - 4 of 4 Chapters
[Characterizing the functional behavior of individual proteins in a variety of different contexts is an important step in understanding life at the molecular level. Endeavors such as understanding biological pathways, investigating disease, and developing drugs to cure those diseases depend on...
[We previously introduced information-theoretic metrics for evaluating classification performance in protein function prediction which we describe here . In this learning scenario, the input space X represents proteins, whereas the output space Y contains directed acyclic graphs describing...
[In this chapter, we first analyze the average information content in a data set of experimentally annotated proteins and then evaluate performance accuracy of different function prediction methods using both topological and probabilistic metrics.]
[Here we introduce an information-theoretic framework for evaluating the performance of computational protein function prediction. We frame protein function prediction as a structured output learning problem in which the output space is represented by consistent subgraphs of the GO graph. We...
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