Probabilistic Modeling in Bioinformatics and Medical Informatics

ISBN: 978-1-85233-778-0 (Print) 978-1-84628-119-8 (Online)

Table of contents (16 chapters)

  1. Probabilistic Modeling

    1. No Access

      Book Chapter

      Pages 3-15

      A Leisurely Look at Statistical Inference

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      Book Chapter

      Pages 17-57

      Introduction to Learning Bayesian Networks from Data

    3. No Access

      Book Chapter

      Pages 59-80

      A Casual View of Multi-Layer Perceptrons as Probability Models

  2. Bioinformatics

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      Book Chapter

      Pages 83-145

      Introduction to Statistical Phylogenetics

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      Book Chapter

      Pages 147-190

      Detecting Recombination in DNA Sequence Alignments

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      Book Chapter

      Pages 191-210

      RNA-Based Phylogenetic Methods

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      Book Chapter

      Pages 211-238

      Statistical Methods in Microarray Gene Expression Data Analysis

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      Book Chapter

      Pages 239-267

      Inferring Genetic Regulatory Networks from Microarray Experiments with Bayesian Networks

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      Book Chapter

      Pages 269-293

      Modeling Genetic Regulatory Networks using Gene Expression Profiling and State-Space Models

  3. Medical Informatics

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      Book Chapter

      Pages 297-349

      An Anthology of Probabilistic Models for Medical Informatics

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      Book Chapter

      Pages 351-370

      Bayesian Analysis of Population Pharmacokinetic/Pharmacodynamic Models

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      Book Chapter

      Pages 371-389

      Assessing the Effectiveness of Bayesian Feature Selection

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      Book Chapter

      Pages 391-417

      Bayes Consistent Classification of EEG Data by Approximate Marginalization

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      Book Chapter

      Pages 419-450

      Ensemble Hidden Markov Models with Extended Observation Densities for Biosignal Analysis

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      Book Chapter

      Pages 451-472

      A Probabilistic Network for Fusion of Data and Knowledge in Clinical Microbiology

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      Book Chapter

      Pages 473-489

      Software for Probability Models in Medical Informatics