Probabilistic Modeling in Bioinformatics and Medical Informatics

Part I. Probabilistic Modeling

1. A Leisurely Look at Statistical Inference
Dirk Husmeier

2. Introduction to Learning Bayesian Networks from Data
Dirk Husmeier

3. A Casual View of Multi-Layer Perceptrons as Probability Models
Richard Dybowski

Part II. Bioinformatics

4. Introduction to Statistical Phylogenetics
Dirk Husmeier

5. Detecting Recombination in DNA Sequence Alignments
Dirk Husmeier, Frank Wright

6. RNA-Based Phylogenetic Methods
Magnus Rattray, Paul G. Higgs

7. Statistical Methods in Microarray Gene Expression Data Analysis
Claus-Dieter Mayer, Chris A. Glasbey

8. Inferring Genetic Regulatory Networks from Microarray Experiments with Bayesian Networks
Dirk Husmeier

9. Modeling Genetic Regulatory Networks using Gene Expression Profiling and State-Space Models
Claudia Rangel, John Angus, Zoubin Ghahramani, David L. Wild

Part III. Medical Informatics

10. An Anthology of Probabilistic Models for Medical Informatics
Richard Dybowski, Stephen Roberts

11. Bayesian Analysis of Population Pharmacokinetic/Pharmacodynamic Models
David J. Lunn

12. Assessing the Effectiveness of Bayesian Feature Selection
Ian T. Nabney, David J. Evans, Yann Brulé, Caroline Gordon

13. Bayes Consistent Classification of EEG Data by Approximate Marginalization
Peter Sykacek, Iead Rezek, Stephen Roberts

14. Ensemble Hidden Markov Models with Extended Observation Densities for Biosignal Analysis
Iead Rezek, Stephen Roberts

15. A Probabilistic Network for Fusion of Data and Knowledge in Clinical Microbiology
Steen Andreassen, Leonard Leibovici, Mical Paul, Anders D. Nielsen, Alina Zalounina, Leif E. Kristensen, Karsten Falborg, Brian Kristensen, Uwe Frank, Henrik C. Schønheyder

16. Software for Probability Models in Medical Informatics
Richard Dybowski

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Avainsanat: COMPUTERS / Computer Science COM014000