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Probabilistic Modeling in Bioinformatics and Medical Informatics

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Cover of 'Probabilistic Modeling in Bioinformatics and Medical Informatics'

Table of Contents

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    Book Overview
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    Chapter 1 A Leisurely Look at Statistical Inference
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    Chapter 2 Introduction to Learning Bayesian Networks from Data
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    Chapter 3 A Casual View of Multi-Layer Perceptrons as Probability Models
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    Chapter 4 Introduction to Statistical Phylogenetics
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    Chapter 5 Detecting Recombination in DNA Sequence Alignments
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    Chapter 6 RNA-Based Phylogenetic Methods
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    Chapter 7 Statistical Methods in Microarray Gene Expression Data Analysis
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    Chapter 8 Inferring Genetic Regulatory Networks from Microarray Experiments with Bayesian Networks
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    Chapter 9 Modeling Genetic Regulatory Networks using Gene Expression Profiling and State-Space Models
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    Chapter 10 An Anthology of Probabilistic Models for Medical Informatics
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    Chapter 11 Bayesian Analysis of Population Pharmacokinetic/Pharmacodynamic Models
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    Chapter 12 Assessing the Effectiveness of Bayesian Feature Selection
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    Chapter 13 Bayes Consistent Classification of EEG Data by Approximate Marginalization
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    Chapter 14 Ensemble Hidden Markov Models with Extended Observation Densities for Biosignal Analysis
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    Chapter 15 A Probabilistic Network for Fusion of Data and Knowledge in Clinical Microbiology
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    Chapter 16 Software for Probability Models in Medical Informatics
Attention for Chapter 6: RNA-Based Phylogenetic Methods
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mendeley
6 Mendeley
Summary
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Chapter title
RNA-Based Phylogenetic Methods
Chapter number 6
Book title
Probabilistic Modeling in Bioinformatics and Medical Informatics
Published by
Springer, London, January 2005
DOI 10.1007/1-84628-119-9_6
Book ISBNs
978-1-85233-778-0, 978-1-84628-119-8
Authors

Magnus Rattray, Paul G. Higgs, Rattray, Magnus, Higgs, Paul G.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 17%
Unknown 5 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 50%
Professor 1 17%
Researcher 1 17%
Unknown 1 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 33%
Computer Science 1 17%
Psychology 1 17%
Engineering 1 17%
Unknown 1 17%

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