Bayesian analysis of gene expression data [[electronic resource] /] / edited by Bani Mallick, David Gold, and Veera Baladandayuthapani |
Autore | Mallick Bani K. <1965-> |
Pubbl/distr/stampa | Hoboken, N.J., : Wiley, 2009 |
Descrizione fisica | 1 online resource (254 p.) |
Disciplina |
572.8
572.86501519542 |
Altri autori (Persone) |
MallickBani K. <1965->
GoldDavid <1970-> BaladandayuthapaniVeerabhadran <1976-> |
Collana | Statistics in practice |
Soggetto topico |
Gene expression - Statistical methods
Bayesian statistical decision theory |
ISBN |
1-282-34942-2
9786612349423 0-470-74278-X 0-470-74281-X |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Bayesian Analysis of Gene Expression Data; Contents; Table of Notation; 1 Bioinformatics and Gene Expression Experiments; 1.1 Introduction; 1.2 About This Book; 2 Gene Expression Data: Basic Biology and Experiments; 2.1 Background Biology; 2.1.1 DNA Structures and Transcription; 2.2 Gene Expression Microarray Experiments; 2.2.1 Microarray Designs; 2.2.2 Work Flow; 2.2.3 Data Cleaning; 3 Bayesian Linear Models for Gene Expression; 3.1 Introduction; 3.2 Bayesian Analysis of a Linear Model; 3.2.1 Analysis via Conjugate Priors; 3.2.2 Bayesian Variable Selection; 3.2.3 Model Selection Priors
3.2.4 Priors on Regression Coefficients3.2.5 Sparsity Priors; 3.3 Bayesian Linear Models for Differential Expression; 3.3.1 Relevant Work; 3.4 Bayesian ANOVA for Gene Selection; 3.4.1 The Basic Bayesian ANOVA Model; 3.4.2 Differential Expression via Model Selection; 3.5 Robust ANOVA model with Mixtures of Singular Distributions; 3.6 Case Study; 3.7 Accounting for Nuisance Effects; 3.8 Summary and Further Reading; 4 Bayesian Multiple Testing and False Discovery Rate Analysis; 4.1 Introduction to Multiple Testing; 4.2 False Discovery Rate Analysis; 4.2.1 Theoretical Developments 4.2.2 FDR Analysis with Gene Expression Arrays4.3 Bayesian False Discovery Rate Analysis; 4.3.1 Theoretical Developments; 4.4 Bayesian Estimation of FDR; 4.5 FDR and Decision Theory; 4.6 FDR and bFDR Summary; 5 Bayesian Classification for Microarray Data; 5.1 Introduction; 5.2 Classification and Discriminant Rules; 5.3 Bayesian Discriminant Analysis; 5.4 Bayesian Regression Based Approaches to Classification; 5.4.1 Bayesian Analysis of Generalized Linear Models; 5.4.2 Link Functions; 5.4.3 GLM using Latent Processes; 5.4.4 Priors and Computation 5.4.5 Bayesian Probit Regression using Auxiliary Variables5.5 Bayesian Nonlinear Classification; 5.5.1 Classification using Interactions; 5.5.2 Classification using Kernel Methods; 5.6 Prediction and Model Choice; 5.7 Examples; 5.8 Discussion; 6 Bayesian Hypothesis Inference for Gene Classes; 6.1 Interpreting Microarray Results; 6.2 Gene Classes; 6.2.1 Enrichment Analysis; 6.3 Bayesian Enrichment Analysis; 6.4 Multivariate Gene Class Detection; 6.4.1 Extending the Bayesian ANOVA Model; 6.4.2 Bayesian Decomposition; 6.5 Summary; 7 Unsupervised Classification and Bayesian Clustering 7.1 Introduction to Bayesian Clustering for Gene Expression Data7.2 Hierarchical Clustering; 7.3 K-Means Clustering; 7.4 Model-Based Clustering; 7.5 Model-Based Agglomerative Hierarchical Clustering; 7.6 Bayesian Clustering; 7.7 Principal Components; 7.8 Mixture Modeling; 7.8.1 Label Switching; 7.9 Clustering Using Dirichlet Process Prior; 7.9.1 Infinite Mixture of Gaussian Distributions; 8 Bayesian Graphical Models; 8.1 Introduction; 8.2 Probabilistic Graphical Models; 8.3 Bayesian Networks; 8.4 Inference for Network Models; 8.4.1 Multinomial-Dirichlet Model; 8.4.2 Gaussian Model 8.4.3 Model Search |
Record Nr. | UNINA-9910139785403321 |
Mallick Bani K. <1965->
![]() |
||
Hoboken, N.J., : Wiley, 2009 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Bayesian analysis of gene expression data [[electronic resource] /] / edited by Bani Mallick, David Gold, and Veera Baladandayuthapani |
Autore | Mallick Bani K. <1965-> |
Pubbl/distr/stampa | Hoboken, N.J., : Wiley, 2009 |
Descrizione fisica | 1 online resource (254 p.) |
Disciplina |
572.8
572.86501519542 |
Altri autori (Persone) |
MallickBani K. <1965->
GoldDavid <1970-> BaladandayuthapaniVeerabhadran <1976-> |
Collana | Statistics in practice |
Soggetto topico |
Gene expression - Statistical methods
Bayesian statistical decision theory |
ISBN |
1-282-34942-2
9786612349423 0-470-74278-X 0-470-74281-X |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Bayesian Analysis of Gene Expression Data; Contents; Table of Notation; 1 Bioinformatics and Gene Expression Experiments; 1.1 Introduction; 1.2 About This Book; 2 Gene Expression Data: Basic Biology and Experiments; 2.1 Background Biology; 2.1.1 DNA Structures and Transcription; 2.2 Gene Expression Microarray Experiments; 2.2.1 Microarray Designs; 2.2.2 Work Flow; 2.2.3 Data Cleaning; 3 Bayesian Linear Models for Gene Expression; 3.1 Introduction; 3.2 Bayesian Analysis of a Linear Model; 3.2.1 Analysis via Conjugate Priors; 3.2.2 Bayesian Variable Selection; 3.2.3 Model Selection Priors
3.2.4 Priors on Regression Coefficients3.2.5 Sparsity Priors; 3.3 Bayesian Linear Models for Differential Expression; 3.3.1 Relevant Work; 3.4 Bayesian ANOVA for Gene Selection; 3.4.1 The Basic Bayesian ANOVA Model; 3.4.2 Differential Expression via Model Selection; 3.5 Robust ANOVA model with Mixtures of Singular Distributions; 3.6 Case Study; 3.7 Accounting for Nuisance Effects; 3.8 Summary and Further Reading; 4 Bayesian Multiple Testing and False Discovery Rate Analysis; 4.1 Introduction to Multiple Testing; 4.2 False Discovery Rate Analysis; 4.2.1 Theoretical Developments 4.2.2 FDR Analysis with Gene Expression Arrays4.3 Bayesian False Discovery Rate Analysis; 4.3.1 Theoretical Developments; 4.4 Bayesian Estimation of FDR; 4.5 FDR and Decision Theory; 4.6 FDR and bFDR Summary; 5 Bayesian Classification for Microarray Data; 5.1 Introduction; 5.2 Classification and Discriminant Rules; 5.3 Bayesian Discriminant Analysis; 5.4 Bayesian Regression Based Approaches to Classification; 5.4.1 Bayesian Analysis of Generalized Linear Models; 5.4.2 Link Functions; 5.4.3 GLM using Latent Processes; 5.4.4 Priors and Computation 5.4.5 Bayesian Probit Regression using Auxiliary Variables5.5 Bayesian Nonlinear Classification; 5.5.1 Classification using Interactions; 5.5.2 Classification using Kernel Methods; 5.6 Prediction and Model Choice; 5.7 Examples; 5.8 Discussion; 6 Bayesian Hypothesis Inference for Gene Classes; 6.1 Interpreting Microarray Results; 6.2 Gene Classes; 6.2.1 Enrichment Analysis; 6.3 Bayesian Enrichment Analysis; 6.4 Multivariate Gene Class Detection; 6.4.1 Extending the Bayesian ANOVA Model; 6.4.2 Bayesian Decomposition; 6.5 Summary; 7 Unsupervised Classification and Bayesian Clustering 7.1 Introduction to Bayesian Clustering for Gene Expression Data7.2 Hierarchical Clustering; 7.3 K-Means Clustering; 7.4 Model-Based Clustering; 7.5 Model-Based Agglomerative Hierarchical Clustering; 7.6 Bayesian Clustering; 7.7 Principal Components; 7.8 Mixture Modeling; 7.8.1 Label Switching; 7.9 Clustering Using Dirichlet Process Prior; 7.9.1 Infinite Mixture of Gaussian Distributions; 8 Bayesian Graphical Models; 8.1 Introduction; 8.2 Probabilistic Graphical Models; 8.3 Bayesian Networks; 8.4 Inference for Network Models; 8.4.1 Multinomial-Dirichlet Model; 8.4.2 Gaussian Model 8.4.3 Model Search |
Record Nr. | UNINA-9910830664603321 |
Mallick Bani K. <1965->
![]() |
||
Hoboken, N.J., : Wiley, 2009 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|