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|a 10.1007/b138794
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|a Probabilistic Modeling in Bioinformatics and Medical Informatics
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|c edited by Dirk Husmeier, Richard Dybowski, Stephen Roberts.
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250 |
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|a 1st ed. 2005.
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264 |
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|a London :
|b Springer London :
|b Imprint: Springer,
|c 2005.
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300 |
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|a XX, 508 p.
|b online resource.
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|a Advanced Information and Knowledge Processing,
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|a Probabilistic Modeling -- A Leisurely Look at Statistical Inference -- to Learning Bayesian Networks from Data -- A Casual View of Multi-Layer Perceptrons as Probability Models -- Bioinformatics -- to Statistical Phylogenetics -- Detecting Recombination in DNA Sequence Alignments -- RNA-Based Phylogenetic Methods -- Statistical Methods in Microarray Gene Expression Data Analysis -- Inferring Genetic Regulatory Networks from Microarray Experiments with Bayesian Networks -- Modeling Genetic Regulatory Networks using Gene Expression Profiling and State-Space Models -- Medical Informatics -- An Anthology of Probabilistic Models for Medical Informatics -- Bayesian Analysis of Population Pharmacokinetic/Pharmacodynamic Models -- Assessing the Effectiveness of Bayesian Feature Selection -- Bayes Consistent Classification of EEG Data by Approximate Marginalization -- Ensemble Hidden Markov Models with Extended Observation Densities for Biosignal Analysis -- A Probabilistic Network for Fusion of Data and Knowledge in Clinical Microbiology -- Software for Probability Models in Medical Informatics.
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|a Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.
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|a Loaded electronically.
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|a Electronic access restricted to members of the Holy Cross Community.
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650 |
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|a Mathematical statistics.
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650 |
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|a Computer science—Mathematics.
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650 |
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|a Algorithms.
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|a Statistics .
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|a Bioinformatics.
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|a Health informatics.
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|a Husmeier, Dirk.
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|a Dybowski, Richard.
|e editor.
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700 |
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|a Roberts, Stephen.
|e editor.
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