Probabilistic Modeling in Bioinformatics and Medical Informatics

Front Cover
Dirk Husmeier, Richard Dybowski, Stephen Roberts
Springer Science & Business Media, Mar 30, 2006 - Computers - 508 pages
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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Contents

A Leisurely Look at Statistical Inference
3
References
15
References
55
References
79
References
142
RNABased Phylogenetic Methods
191
References
208
Statistical Methods in Microarray Gene Expression Data
211
Bayesian Analysis of Population
351
References
369
References
388
References
416
A Model Free Update Equations
442
References
449
Probabilities for Sepsis and Pathogens
456
References
470

References
235
References
265
References
291
References
487
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About the author (2006)

Husmeier, Imperial College, London, UK.

Stephen Roberts is a Fellow of the Institute for Advanced Research in Arts and Social Sciences at the University of Birmingham. He has written or edited a number of well-known books on Chartism and related subjects.