Titlebook: Information-Theoretic Evaluation for Computational Biomedical Ontologies; Wyatt Travis Clark Book 2014 The Author(s) 2014 Algorithm Develo

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Methods,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 protein function according to the Gene Ontology (GO).

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Experiments and Results,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.

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Information-Theoretic Evaluation for Computational Biomedical Ontologies978-3-319-04138-4Series ISSN 2191-5768 Series E-ISSN 2191-5776

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Book 2014 performance is difficult due to problems caused by the structure of biomedical ontologies and incomplete annotations of genes. This work proposes an information-theoretic framework to evaluate the performance of computational protein function prediction. A Bayesian network is used, structured accor

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https://doi.org/10.1007/978-3-030-04600-2n at critical points, are only approximate with regard to global failure of a lamina and failure progression to ultimate failure of a multi-directional laminate. For these reasons a macromechanical approach to failure analysis is preferred.

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Limited Versus Extended Lymphadenectomy,long-term survival. It gives additional consideration to lymphadenectomy in the context of mucosal disease. The chapter also highlights some of the problems with definitions in published literature and the non-standardised processing of specimens.

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Computing Colour Image Processinghermore, the production of GPC is also affected by the curing time and curing temperature. Few studies have also been carried out to observe the effect of curing temperature on the polymerisation reaction of GPC.