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Probabilistic Modeling in Bioinformatics and Medical Informatics
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 part...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Springer London : Imprint: Springer,
2005.
|
| Edición: | 1st ed. 2005. |
| Colección: | Advanced Information and Knowledge Processing,
|
| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- 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.