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03790nam a22005895i 4500 |
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|a 9781846281198
|9 978-1-84628-119-8
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|a 10.1007/b138794
|2 doi
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|a QA276-280
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|a COM077000
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|a 005.55
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|a Probabilistic Modeling in Bioinformatics and Medical Informatics
|h [electronic resource] /
|c edited by Dirk Husmeier, Richard Dybowski, Stephen Roberts.
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|a London :
|b Springer London,
|c 2005.
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|a XX, 508 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
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|a online resource
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|a text file
|b PDF
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|a Advanced Information and Knowledge Processing
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|a 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.
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|a 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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|a Computer science.
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|a Health informatics.
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|a Algorithms.
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|a Mathematical statistics.
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|a Computer science
|x Mathematics.
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|a Bioinformatics.
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|a Statistics.
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|a Computer Science.
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|a Probability and Statistics in Computer Science.
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|a Math Applications in Computer Science.
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|a Algorithm Analysis and Problem Complexity.
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|a Statistics for Life Sciences, Medicine, Health Sciences.
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|a Bioinformatics.
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|a Health Informatics.
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|a Husmeier, Dirk.
|e editor.
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|a Dybowski, Richard.
|e editor.
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|a Roberts, Stephen.
|e editor.
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2 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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776 |
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|i Printed edition:
|z 9781852337780
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|a Advanced Information and Knowledge Processing
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|u http://dx.doi.org/10.1007/b138794
|z Full Text via HEAL-Link
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|a ZDB-2-SCS
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950 |
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|a Computer Science (Springer-11645)
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