E Book

Probabilistic Modeling in Bioinformatics and Medical Informatics

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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.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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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

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Penerbit

London : Springer., 2005

Deskripsi Fisik

XX, 508 p.online resource.

Bahasa

English

ISBN/ISSN

9781846281198

Klasifikasi

005.55

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

1st ed.

Subjek

Bioinformatics.
Algorithms.
Algorithm Analysis and Problem Complexity.
Health informatics.
Computer science—Mathematics.
Math Applications in Computer Science.
Statistics .
Mathematical statistics.
Probability and Statistics in Computer Science.
Statistics for Life Sciences, Medicine, Health Sciences.

Info Detail Spesifik

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Pernyataan Tanggungjawab

Dirk Husmeier, Richard Dybowski, Stephen Roberts.

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