東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Bayesian modeling in bioinformatics

Dey, Dipak.

FindBook

Google Book

Amazon

博客來

Bayesian modeling in bioinformatics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Bayesian modeling in bioinformatics/ edited by Dipak K. Dey, Samiran Ghosh, Bani K. Mallick.
其他作者:	Dey, Dipak.
出版者:	Boca Raton :CRC Press, : c2011.,
面頁冊數:	1 online resource (xxv, 440 p.) :ill.
附註:	"A Chapman & Hall book."
內容註:	List of Tables -- List of Figures -- Preface -- Symbol Description -- Chapter 1: Estimation and Testing in Time-Course Microarray Experiments -- Chapter 2: Classification for Differential Gene Expression Using Bayesian Hierarchical Models -- Chapter 3: Applications of the Mode Oriented Stochastic Search (MOSS) Algorithm for Discrete Multi-Way Data to Genomewide Studies -- Chapter 4: Nonparametric Bayesian Bioinformatics -- Chapter 5: Measurement Error and Survival Model for cDNA Microarrays -- Chapter 6: Bayesian Robust Inference for Differential Gene Expression.
標題:	Bayes Theorem. -
電子資源:	http://www.crcnetbase.com/isbn/9781420070170
ISBN:	9781420070187 (electronic bk.)

Bayesian modeling in bioinformatics
Bayesian modeling in bioinformatics[electronic resource] /edited by Dipak K. Dey, Samiran Ghosh, Bani K. Mallick. - Boca Raton :CRC Press,c2011. - 1 online resource (xxv, 440 p.) :ill. - Chapman & Hall/CRC biostatistics series ;34. - Chapman & Hall/CRC biostatistics series ;29..

"A Chapman & Hall book."

Includes bibliographical references and index.

List of Tables -- List of Figures -- Preface -- Symbol Description -- Chapter 1: Estimation and Testing in Time-Course Microarray Experiments -- Chapter 2: Classification for Differential Gene Expression Using Bayesian Hierarchical Models -- Chapter 3: Applications of the Mode Oriented Stochastic Search (MOSS) Algorithm for Discrete Multi-Way Data to Genomewide Studies -- Chapter 4: Nonparametric Bayesian Bioinformatics -- Chapter 5: Measurement Error and Survival Model for cDNA Microarrays -- Chapter 6: Bayesian Robust Inference for Differential Gene Expression.

"Bayesian Modeling in Bioinformatics" discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research, such as cancer. It presents a broad overview of statistical inference, clustering, and classification problems in two main high-throughput platforms: microarray gene expression and phylogenic analysis. The book explores Bayesian techniques and models for detecting differentially expressed genes, classifying differential gene expression, and identifying biomarkers. It develops novel Bayesian nonparametric approaches for bioinformatics problems, measurement error and survival models for cDNA microarrays, a Bayesian hidden Markov modeling approach for CGH array data, Bayesian approaches for phylogenic analysis, sparsity priors for protein-protein interaction predictions, and Bayesian networks for gene expression data. The text also describes applications of mode-oriented stochastic search algorithms, in vitro to in vivo factor profiling, proportional hazards regression using Bayesian kernel machines, and QTL mapping.

ISBN: 9781420070187 (electronic bk.)Subjects--Topical Terms:

709996
Bayes Theorem.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: QH324.2 / .D49 2011eb

Dewey Class. No.: 570.285

National Library of Medicine Call No.: QH 324.2

Bayesian modeling in bioinformatics
LDR:02830cmm a2200301Ka 4500 001 1902098
003 OCoLC
005 20140108090635.0
006 m o d
007 cr cnu---unuuu
008 240124s2011 flua ob 001 0 eng d
020 $a 9781420070187 (electronic bk.)
020 $a 1420070185 (electronic bk.)
035 $a ocn671643968
035 $a 1902098
040 $a N $b eng $c N $d YDXCP $d EBLCP $d CDX $d E7B $d OCLCQ $d MHW $d OCLCQ $d OHS $d OCLCQ $d DEBSZ $d OCLCQ $d CUS $d KUT
050 4 $a QH324.2 $b .D49 2011eb
060 4 $a QH 324.2
082 0 4 $a 570.285 $2 22
245 0 0 $a Bayesian modeling in bioinformatics $h [electronic resource] / $c edited by Dipak K. Dey, Samiran Ghosh, Bani K. Mallick.
260 $a Boca Raton : $b CRC Press, $c c2011.
300 $a 1 online resource (xxv, 440 p.) : $b ill.
490 1 $a Chapman & Hall/CRC biostatistics series ; $v 34
500 $a "A Chapman & Hall book."
504 $a Includes bibliographical references and index.
505 0 $a List of Tables -- List of Figures -- Preface -- Symbol Description -- Chapter 1: Estimation and Testing in Time-Course Microarray Experiments -- Chapter 2: Classification for Differential Gene Expression Using Bayesian Hierarchical Models -- Chapter 3: Applications of the Mode Oriented Stochastic Search (MOSS) Algorithm for Discrete Multi-Way Data to Genomewide Studies -- Chapter 4: Nonparametric Bayesian Bioinformatics -- Chapter 5: Measurement Error and Survival Model for cDNA Microarrays -- Chapter 6: Bayesian Robust Inference for Differential Gene Expression.
520 $a "Bayesian Modeling in Bioinformatics" discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research, such as cancer. It presents a broad overview of statistical inference, clustering, and classification problems in two main high-throughput platforms: microarray gene expression and phylogenic analysis. The book explores Bayesian techniques and models for detecting differentially expressed genes, classifying differential gene expression, and identifying biomarkers. It develops novel Bayesian nonparametric approaches for bioinformatics problems, measurement error and survival models for cDNA microarrays, a Bayesian hidden Markov modeling approach for CGH array data, Bayesian approaches for phylogenic analysis, sparsity priors for protein-protein interaction predictions, and Bayesian networks for gene expression data. The text also describes applications of mode-oriented stochastic search algorithms, in vitro to in vivo factor profiling, proportional hazards regression using Bayesian kernel machines, and QTL mapping.
588 $a Description based on print version record.
650 1 2 $a Bayes Theorem. $3 709996
650 2 2 $a Computational Biology. $3 736565
650 2 2 $a Models, Biological. $3 714574
650 0 $a Bioinformatics $x Statistical methods. $3 590632
650 0 $a Bayesian statistical decision theory. $3 551404
655 0 $a Electronic books. $2 lcsh $3 542853
700 1 $a Dey, Dipak. $3 2018154
700 1 $a Ghosh, Samiran. $3 1923067
700 1 $a Mallick, Bani K., $d 1965- $3 2018155
830 0 $a Chapman & Hall/CRC biostatistics series ; $v 29. $3 3652254
856 4 0 $u http://www.crcnetbase.com/isbn/9781420070170