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Detalles bibliogr�ficos

T�tulo

Bayesian Inference for Gene Expression and Proteomics

Editor

Cambridge University Press 00/l /24 J

Fecha de publicaci�n

2006

Idioma

Ingl�s

ISBN 10

052186092X

ISBN 13

9780521860925

Encuadernaci�n

Encuadernaci�n de tapa dura

Estado

Very Good

Cat�logos de vendedores

Acerca de

Sinopsis

Expert overviews of Bayesian methodology, tools and software for multi-platform high-throughput experimentation.

Acerca de los autores

Kim-Anh Do is a Professor in the Department of Biostatistics and Applied Mathematics at the University of Texas M. D. Anderson Cancer Center. Her research interests are in computer-intensive statistical methods with recent focus in the development of methodology and software to analyze data produced from high-throughput optimization.

Peter M�ller is a Professor in the Department of Biostatistics and Applied Mathematics at the University of Texas M. D. Anderson Cancer Center. His research interests and contributions are in the areas of Markov chain Monte Carlo posterior simulation, nonparametric Bayesian inference, hierarchical models, mixture models and Bayesian decisions problems.

Marina Vannucci is a Professor of Statistics at Rice University. Her research focuses on the theory and practice of Bayesian variable selection techniques and on the development of wavelet-based statistical models and their applications. Her work is often motivated by real problems that need to be addressed with suitable statistical methods.

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