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Analyzing microarray gene expression data [[electronic resource] /] / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise
| Analyzing microarray gene expression data [[electronic resource] /] / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise |
| Autore | McLachlan Geoffrey J. <1946-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2004 |
| Descrizione fisica | 1 online resource (366 p.) |
| Disciplina |
572.8636
572.865 |
| Altri autori (Persone) |
DoKim-Anh <1960->
AmbroiseChristophe <1969-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
DNA microarrays - Statistical methods
Gene expression - Statistical methods |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-25332-0
9786610253326 0-470-35030-X 0-471-72612-5 0-471-72842-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Analyzing Microarray Gene Expression Data; Contents; Preface; 1 Microarrays in Gene Expression Studies; 1.1 Introduction; 1.2 Background Biology; 1.2.1 Genome, Genotype, and Gene Expression; 1.2.2 Of Wild-Types and Other Alleles; 1.2.3 Aspects of Underlying Biology and Physiochemistry; 1.3 Polymerase Chain Reaction; 1.4 cDNA; 1.4.1 Expressed Sequence Tag; 1.5 Microarray Technology and Application; 1.5.1 History of Microarray Development; 1.5.2 Tools of Microarray Technology; 1.5.3 Limitations of Microarray Technology; 1.5.4 Oligonucleotides versus cDNA Arrays
1.5.5 SAGE: Another Method for Detecting and Measuring Gene Expression Levels1.5.6 Emerging Technologies; 1.6 Sampling of Relevant Research Entities and Public Resources; 2 Cleaning and Normalization; 2.1 Introduction; 2.2 Cleaning Procedures; 2.2.1 Image Processing to Extract Information; 2.2.2 Missing Value Estimation; 2.2.3 Sources of Nonlinearity; 2.3 Normalization and Plotting Procedures for Oligonucleotide Arrays; 2.3.1 Global Approaches for Oligonucleotide Array Data; 2.3.2 Spiked Standard Approaches; 2.3.3 Geometric Mean and Linear Regression Normalization for Multiple Arrays 2.3.4 Nonlinear Normalization for Multiple Arrays Using Smooth Curves2.4 Normalization Methods for cDNA Microarray Data; 2.4.1 Single-Array Normalization; 2.4.2 Multiple Slides Normalization; 2.4.3 ANOVA and Related Methods for Normalization; 2.4.4 Mixed-Model Method for Normalization; 2.4.5 SNOMAD; 2.5 Transformations and Replication; 2.5.1 Importance of Replication; 2.5.2 Transformations; 2.6 Analysis of the Alon Data Set; 2.7 Comparison of Normalization Strategies and Discussion; 3 Some Cluster Analysis Methods; 3.1 Introduction; 3.2 Reduction in the Dimension of the Feature Space 3.3 Cluster Analysis3.4 Some Hierarchical Agglomerative Techniques; 3.5 k-Means Clustering; 3.6 Cluster Analysis with No A Priori Metric; 3.7 Clustering via Finite Mixture Models; 3.7.1 Definition; 3.7.2 Advantages of Model-Based Clustering; 3.8 Fitting Mixture Models Via the EM Algorithm; 3.8.1 E-Step; 3.8.2 M-Step; 3.8.3 Choice of Starting Values for the EM Algorithm; 3.9 Clustering Via Normal Mixtures; 3.9.1 Heteroscedastic Components; 3.9.2 Homoscedastic Components; 3.9.3 Spherical Components; 3.9.4 Choice of Root; 3.9.5 Available Software; 3.10 Mixtures of t Distributions 3.11 Mixtures of Factor Analyzers3.12 Choice of Clustering Solution; 3.13 Classification ML Approach; 3.14 Mixture Models for Clinical and Microarray Data; 3.14.1 Unconditional Approach; 3.14.2 Conditional Approach; 3.15 Choice of the Number of Components in a Mixture Model; 3.15.1 Order of a Mixture Model; 3.15.2 Approaches for Assessing Mixture Order; 3.15.3 Bayesian Information Criterion; 3.15.4 Integrated Classification Likelihood Criterion; 3.16 Resampling Approach; 3.17 Other Resampling Approaches for Number of Clusters; 3.17.1 The Gap Statistic 3.17.2 The Clest Method for the Number of Clusters |
| Record Nr. | UNINA-9910146082203321 |
McLachlan Geoffrey J. <1946->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Analyzing microarray gene expression data [[electronic resource] /] / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise
| Analyzing microarray gene expression data [[electronic resource] /] / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise |
| Autore | McLachlan Geoffrey J. <1946-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2004 |
| Descrizione fisica | 1 online resource (366 p.) |
| Disciplina |
572.8636
572.865 |
| Altri autori (Persone) |
DoKim-Anh <1960->
AmbroiseChristophe <1969-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
DNA microarrays - Statistical methods
Gene expression - Statistical methods |
| ISBN |
1-280-25332-0
9786610253326 0-470-35030-X 0-471-72612-5 0-471-72842-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Analyzing Microarray Gene Expression Data; Contents; Preface; 1 Microarrays in Gene Expression Studies; 1.1 Introduction; 1.2 Background Biology; 1.2.1 Genome, Genotype, and Gene Expression; 1.2.2 Of Wild-Types and Other Alleles; 1.2.3 Aspects of Underlying Biology and Physiochemistry; 1.3 Polymerase Chain Reaction; 1.4 cDNA; 1.4.1 Expressed Sequence Tag; 1.5 Microarray Technology and Application; 1.5.1 History of Microarray Development; 1.5.2 Tools of Microarray Technology; 1.5.3 Limitations of Microarray Technology; 1.5.4 Oligonucleotides versus cDNA Arrays
1.5.5 SAGE: Another Method for Detecting and Measuring Gene Expression Levels1.5.6 Emerging Technologies; 1.6 Sampling of Relevant Research Entities and Public Resources; 2 Cleaning and Normalization; 2.1 Introduction; 2.2 Cleaning Procedures; 2.2.1 Image Processing to Extract Information; 2.2.2 Missing Value Estimation; 2.2.3 Sources of Nonlinearity; 2.3 Normalization and Plotting Procedures for Oligonucleotide Arrays; 2.3.1 Global Approaches for Oligonucleotide Array Data; 2.3.2 Spiked Standard Approaches; 2.3.3 Geometric Mean and Linear Regression Normalization for Multiple Arrays 2.3.4 Nonlinear Normalization for Multiple Arrays Using Smooth Curves2.4 Normalization Methods for cDNA Microarray Data; 2.4.1 Single-Array Normalization; 2.4.2 Multiple Slides Normalization; 2.4.3 ANOVA and Related Methods for Normalization; 2.4.4 Mixed-Model Method for Normalization; 2.4.5 SNOMAD; 2.5 Transformations and Replication; 2.5.1 Importance of Replication; 2.5.2 Transformations; 2.6 Analysis of the Alon Data Set; 2.7 Comparison of Normalization Strategies and Discussion; 3 Some Cluster Analysis Methods; 3.1 Introduction; 3.2 Reduction in the Dimension of the Feature Space 3.3 Cluster Analysis3.4 Some Hierarchical Agglomerative Techniques; 3.5 k-Means Clustering; 3.6 Cluster Analysis with No A Priori Metric; 3.7 Clustering via Finite Mixture Models; 3.7.1 Definition; 3.7.2 Advantages of Model-Based Clustering; 3.8 Fitting Mixture Models Via the EM Algorithm; 3.8.1 E-Step; 3.8.2 M-Step; 3.8.3 Choice of Starting Values for the EM Algorithm; 3.9 Clustering Via Normal Mixtures; 3.9.1 Heteroscedastic Components; 3.9.2 Homoscedastic Components; 3.9.3 Spherical Components; 3.9.4 Choice of Root; 3.9.5 Available Software; 3.10 Mixtures of t Distributions 3.11 Mixtures of Factor Analyzers3.12 Choice of Clustering Solution; 3.13 Classification ML Approach; 3.14 Mixture Models for Clinical and Microarray Data; 3.14.1 Unconditional Approach; 3.14.2 Conditional Approach; 3.15 Choice of the Number of Components in a Mixture Model; 3.15.1 Order of a Mixture Model; 3.15.2 Approaches for Assessing Mixture Order; 3.15.3 Bayesian Information Criterion; 3.15.4 Integrated Classification Likelihood Criterion; 3.16 Resampling Approach; 3.17 Other Resampling Approaches for Number of Clusters; 3.17.1 The Gap Statistic 3.17.2 The Clest Method for the Number of Clusters |
| Record Nr. | UNINA-9910830637803321 |
|
McLachlan Geoffrey J. <1946->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Analyzing microarray gene expression data / / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise
| Analyzing microarray gene expression data / / Geoffrey J. McLachlan, Kim-Anh Do, Christopher Ambroise |
| Autore | McLachlan Geoffrey J. <1946-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2004 |
| Descrizione fisica | 1 online resource (366 p.) |
| Disciplina | 572.8/636 |
| Altri autori (Persone) |
DoKim-Anh <1960->
AmbroiseChristophe <1969-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
DNA microarrays - Statistical methods
Gene expression - Statistical methods |
| ISBN |
1-280-25332-0
9786610253326 0-470-35030-X 0-471-72612-5 0-471-72842-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Analyzing Microarray Gene Expression Data; Contents; Preface; 1 Microarrays in Gene Expression Studies; 1.1 Introduction; 1.2 Background Biology; 1.2.1 Genome, Genotype, and Gene Expression; 1.2.2 Of Wild-Types and Other Alleles; 1.2.3 Aspects of Underlying Biology and Physiochemistry; 1.3 Polymerase Chain Reaction; 1.4 cDNA; 1.4.1 Expressed Sequence Tag; 1.5 Microarray Technology and Application; 1.5.1 History of Microarray Development; 1.5.2 Tools of Microarray Technology; 1.5.3 Limitations of Microarray Technology; 1.5.4 Oligonucleotides versus cDNA Arrays
1.5.5 SAGE: Another Method for Detecting and Measuring Gene Expression Levels1.5.6 Emerging Technologies; 1.6 Sampling of Relevant Research Entities and Public Resources; 2 Cleaning and Normalization; 2.1 Introduction; 2.2 Cleaning Procedures; 2.2.1 Image Processing to Extract Information; 2.2.2 Missing Value Estimation; 2.2.3 Sources of Nonlinearity; 2.3 Normalization and Plotting Procedures for Oligonucleotide Arrays; 2.3.1 Global Approaches for Oligonucleotide Array Data; 2.3.2 Spiked Standard Approaches; 2.3.3 Geometric Mean and Linear Regression Normalization for Multiple Arrays 2.3.4 Nonlinear Normalization for Multiple Arrays Using Smooth Curves2.4 Normalization Methods for cDNA Microarray Data; 2.4.1 Single-Array Normalization; 2.4.2 Multiple Slides Normalization; 2.4.3 ANOVA and Related Methods for Normalization; 2.4.4 Mixed-Model Method for Normalization; 2.4.5 SNOMAD; 2.5 Transformations and Replication; 2.5.1 Importance of Replication; 2.5.2 Transformations; 2.6 Analysis of the Alon Data Set; 2.7 Comparison of Normalization Strategies and Discussion; 3 Some Cluster Analysis Methods; 3.1 Introduction; 3.2 Reduction in the Dimension of the Feature Space 3.3 Cluster Analysis3.4 Some Hierarchical Agglomerative Techniques; 3.5 k-Means Clustering; 3.6 Cluster Analysis with No A Priori Metric; 3.7 Clustering via Finite Mixture Models; 3.7.1 Definition; 3.7.2 Advantages of Model-Based Clustering; 3.8 Fitting Mixture Models Via the EM Algorithm; 3.8.1 E-Step; 3.8.2 M-Step; 3.8.3 Choice of Starting Values for the EM Algorithm; 3.9 Clustering Via Normal Mixtures; 3.9.1 Heteroscedastic Components; 3.9.2 Homoscedastic Components; 3.9.3 Spherical Components; 3.9.4 Choice of Root; 3.9.5 Available Software; 3.10 Mixtures of t Distributions 3.11 Mixtures of Factor Analyzers3.12 Choice of Clustering Solution; 3.13 Classification ML Approach; 3.14 Mixture Models for Clinical and Microarray Data; 3.14.1 Unconditional Approach; 3.14.2 Conditional Approach; 3.15 Choice of the Number of Components in a Mixture Model; 3.15.1 Order of a Mixture Model; 3.15.2 Approaches for Assessing Mixture Order; 3.15.3 Bayesian Information Criterion; 3.15.4 Integrated Classification Likelihood Criterion; 3.16 Resampling Approach; 3.17 Other Resampling Approaches for Number of Clusters; 3.17.1 The Gap Statistic 3.17.2 The Clest Method for the Number of Clusters |
| Record Nr. | UNINA-9910877596703321 |
|
McLachlan Geoffrey J. <1946->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applications of toxicogenomic technologies to predictive toxicology and risk assessment [[electronic resource] /] / Committee on Applications of Toxicogenomic Technologies to Predictive Toxicology ; Board on Environmental Studies and Toxicology ; Board on Life Studies ; Division on Earth and Life Studies ; National Research Council of the National Academies
| Applications of toxicogenomic technologies to predictive toxicology and risk assessment [[electronic resource] /] / Committee on Applications of Toxicogenomic Technologies to Predictive Toxicology ; Board on Environmental Studies and Toxicology ; Board on Life Studies ; Division on Earth and Life Studies ; National Research Council of the National Academies |
| Pubbl/distr/stampa | Washington, D.C., : National Academies Press, c2007 |
| Descrizione fisica | 1 online resource (299 p.) |
| Disciplina | 616/.042 |
| Soggetto topico |
Genetic toxicology
DNA microarrays - Statistical methods Health risk assessment Carcinogenesis |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-10990-8
9786611109905 0-309-11299-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910452115503321 |
| Washington, D.C., : National Academies Press, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applications of toxicogenomic technologies to predictive toxicology and risk assessment [[electronic resource] /] / Committee on Applications of Toxicogenomic Technologies to Predictive Toxicology ; Board on Environmental Studies and Toxicology ; Board on Life Studies ; Division on Earth and Life Studies ; National Research Council of the National Academies
| Applications of toxicogenomic technologies to predictive toxicology and risk assessment [[electronic resource] /] / Committee on Applications of Toxicogenomic Technologies to Predictive Toxicology ; Board on Environmental Studies and Toxicology ; Board on Life Studies ; Division on Earth and Life Studies ; National Research Council of the National Academies |
| Pubbl/distr/stampa | Washington, D.C., : National Academies Press, c2007 |
| Descrizione fisica | 1 online resource (299 p.) |
| Disciplina | 616/.042 |
| Soggetto topico |
Genetic toxicology
DNA microarrays - Statistical methods Health risk assessment Carcinogenesis |
| ISBN |
0-309-17889-4
1-281-10990-8 9786611109905 0-309-11299-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Toxicogenomic technologies -- Experimental design and data analysis -- Application to exposure assessment -- Application to hazard screening -- Application to analyzing variation in human susceptibility -- Application to the study of mechanisms of action -- Other potential applications of toxicogenomic technologies to risk assessment -- Validation -- Sample and data collection and analysis -- Ethical, legal, and social issues -- Conculsions and recommendations. |
| Record Nr. | UNINA-9910778274603321 |
| Washington, D.C., : National Academies Press, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applications of toxicogenomic technologies to predictive toxicology and risk assessment / / Committee on Applications of Toxicogenomic Technologies to Predictive Toxicology ; Board on Environmental Studies and Toxicology ; Board on Life Studies ; Division on Earth and Life Studies ; National Research Council of the National Academies
| Applications of toxicogenomic technologies to predictive toxicology and risk assessment / / Committee on Applications of Toxicogenomic Technologies to Predictive Toxicology ; Board on Environmental Studies and Toxicology ; Board on Life Studies ; Division on Earth and Life Studies ; National Research Council of the National Academies |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Washington, D.C., : National Academies Press, c2007 |
| Descrizione fisica | 1 online resource (299 p.) |
| Disciplina | 616/.042 |
| Soggetto topico |
Genetic toxicology
DNA microarrays - Statistical methods Health risk assessment Carcinogenesis |
| ISBN |
0-309-17889-4
1-281-10990-8 9786611109905 0-309-11299-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Toxicogenomic technologies -- Experimental design and data analysis -- Application to exposure assessment -- Application to hazard screening -- Application to analyzing variation in human susceptibility -- Application to the study of mechanisms of action -- Other potential applications of toxicogenomic technologies to risk assessment -- Validation -- Sample and data collection and analysis -- Ethical, legal, and social issues -- Conculsions and recommendations. |
| Record Nr. | UNINA-9910824330703321 |
| Washington, D.C., : National Academies Press, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Exploration and analysis of DNA microarray and protein array data [[electronic resource] /] / Dhammika Amaratunga, Javier Cabrera
| Exploration and analysis of DNA microarray and protein array data [[electronic resource] /] / Dhammika Amaratunga, Javier Cabrera |
| Autore | Amaratunga Dhammika <1956-> |
| Pubbl/distr/stampa | Hoboken, NJ, : John Wiley, c2004 |
| Descrizione fisica | 1 online resource (270 p.) |
| Disciplina |
572.8
572.8636 |
| Altri autori (Persone) | CabreraJavier |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
DNA microarrays - Statistical methods
Protein microarrays - Statistical methods |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-282-30744-4
9786612307447 0-470-31712-4 0-470-31796-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Exploration and Analysis of DNA Microarray and Protein A rray Data; Contents; Preface; 1. A Brief Introduction; 1.1. A Note on Exploratory Data Analysis; 1.2. Computing Considerations and Software; 1.3. A Brief Outline of the Book; 2. Genomics Basics; 2.1. Genes; 2.2. DNA; 2.3. Gene Expression; 2.4. Hybridization Assays and Other Laboratory Techniques; 2.5. The Human Genome; 2.6. Genome Variations and Their Consequences; 2.7. Genomics; 2.8. The Role of Genomics in Pharmaceutical Research; 2.9. Proteins; 2.10. Bioinformatics; Supplementary Reading; Exercises; 3. Microarrays
3.1. Types of Microarray Experiments3.1.1. Experiment Type 1: Tissue-Specific Gene Expression; 3.1.2. Experiment Type 2: Developmental Genetics; 3.1.3. Experiment Type 3: Genetic Diseases; 3.1.4. Experiment Type 4: Complex Diseases; 3.1.5. Experiment Type 5: Pharmacological Agents; 3.1.6. Experiment Type 6: Plant Breeding; 3.1.7. Experiment Type 7: Environmental Monitoring; 3.2. A Very Simple Hypothetical Microarray Experiment; 3.3. A Typical Microarray Experiment; 3.3.1. Microarray Preparation; 3.3.2. Sample Preparation; 3.3.3. The Hybridization Step; 3.3.4. Scanning the Microarray 3.3.5. Interpreting the Scanned Image3.4. Multichannel cDNA Microarrays; 3.5. Oligonucleotide Arrays; 3.6. Bead-Based Arrays; 3.7. Confirmation of Microarray Results; Supplementary Reading and Electronic References; Exercises; 4. Processing the Scanned Image; 4.1. Converting the Scanned Image to the Spotted Image; 4.1.1. Gridding; 4.1.2. Segmentation; 4.1.3. Quantification; 4.2. Quality Assessment; 4.2.1. Visualizing the Spotted Image; 4.2.2. Numerical Evaluation of Array Quality; 4.2.3. Spatial Problems; 4.2.4. Spatial Randomness; 4.2.5. Quality Control of Arrays 4.2.6. Assessment of Spot Quality4.3. Adjusting for Background; 4.3.1. Estimating the Background; 4.3.2. Adjusting for the Estimated Background; 4.4. Expression Level Calculation for Two-Channel cDNA Microarrays; 4.5. Expression Level Calculation for Oligonucleotide Arrays; 4.5.1. The Average Difference; 4.5.2. A Weighted Average Difference; 4.5.3. Perfect Matches Only; 4.5.4. Background Adjustment Approach; 4.5.5. Model-Based Approach; 4.5.6. Absent-Present Calls; Supplementary Reading; Exercises; 5. Preprocessing Microarray Data; 5.1. Logarithmic Transformation 5.2. Variance Stabilizing Transformations5.3. Sources of Bias; 5.4. Normalization; 5.5. Intensity-Dependent Normalization; 5.5.1. Smooth Function Normalization; 5.5.2. Quantile Normalization; 5.5.3. Normalization of Oligonucleotide Arrays; 5.5.4. Normalization of Two-Channel Arrays; 5.5.5. Spatial Normalization; 5.5.6. Stagewise Normalization; 5.6. Judging the Success of a Normalization; 5.7. Outlier Identification; 5.7.1 Nonresistant Rules for Outlier Identification; 5.7.2. Resistant Rules for Outlier Identification; 5.8. Assessing Replicate Array Quality; Exercises; 6. Summarization 6.1. Replication |
| Record Nr. | UNINA-9910144683203321 |
|
Amaratunga Dhammika <1956->
|
||
| Hoboken, NJ, : John Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Exploration and analysis of DNA microarray and protein array data [[electronic resource] /] / Dhammika Amaratunga, Javier Cabrera
| Exploration and analysis of DNA microarray and protein array data [[electronic resource] /] / Dhammika Amaratunga, Javier Cabrera |
| Autore | Amaratunga Dhammika <1956-> |
| Pubbl/distr/stampa | Hoboken, NJ, : John Wiley, c2004 |
| Descrizione fisica | 1 online resource (270 p.) |
| Disciplina |
572.8
572.8636 |
| Altri autori (Persone) | CabreraJavier |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
DNA microarrays - Statistical methods
Protein microarrays - Statistical methods |
| ISBN |
1-282-30744-4
9786612307447 0-470-31712-4 0-470-31796-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Exploration and Analysis of DNA Microarray and Protein A rray Data; Contents; Preface; 1. A Brief Introduction; 1.1. A Note on Exploratory Data Analysis; 1.2. Computing Considerations and Software; 1.3. A Brief Outline of the Book; 2. Genomics Basics; 2.1. Genes; 2.2. DNA; 2.3. Gene Expression; 2.4. Hybridization Assays and Other Laboratory Techniques; 2.5. The Human Genome; 2.6. Genome Variations and Their Consequences; 2.7. Genomics; 2.8. The Role of Genomics in Pharmaceutical Research; 2.9. Proteins; 2.10. Bioinformatics; Supplementary Reading; Exercises; 3. Microarrays
3.1. Types of Microarray Experiments3.1.1. Experiment Type 1: Tissue-Specific Gene Expression; 3.1.2. Experiment Type 2: Developmental Genetics; 3.1.3. Experiment Type 3: Genetic Diseases; 3.1.4. Experiment Type 4: Complex Diseases; 3.1.5. Experiment Type 5: Pharmacological Agents; 3.1.6. Experiment Type 6: Plant Breeding; 3.1.7. Experiment Type 7: Environmental Monitoring; 3.2. A Very Simple Hypothetical Microarray Experiment; 3.3. A Typical Microarray Experiment; 3.3.1. Microarray Preparation; 3.3.2. Sample Preparation; 3.3.3. The Hybridization Step; 3.3.4. Scanning the Microarray 3.3.5. Interpreting the Scanned Image3.4. Multichannel cDNA Microarrays; 3.5. Oligonucleotide Arrays; 3.6. Bead-Based Arrays; 3.7. Confirmation of Microarray Results; Supplementary Reading and Electronic References; Exercises; 4. Processing the Scanned Image; 4.1. Converting the Scanned Image to the Spotted Image; 4.1.1. Gridding; 4.1.2. Segmentation; 4.1.3. Quantification; 4.2. Quality Assessment; 4.2.1. Visualizing the Spotted Image; 4.2.2. Numerical Evaluation of Array Quality; 4.2.3. Spatial Problems; 4.2.4. Spatial Randomness; 4.2.5. Quality Control of Arrays 4.2.6. Assessment of Spot Quality4.3. Adjusting for Background; 4.3.1. Estimating the Background; 4.3.2. Adjusting for the Estimated Background; 4.4. Expression Level Calculation for Two-Channel cDNA Microarrays; 4.5. Expression Level Calculation for Oligonucleotide Arrays; 4.5.1. The Average Difference; 4.5.2. A Weighted Average Difference; 4.5.3. Perfect Matches Only; 4.5.4. Background Adjustment Approach; 4.5.5. Model-Based Approach; 4.5.6. Absent-Present Calls; Supplementary Reading; Exercises; 5. Preprocessing Microarray Data; 5.1. Logarithmic Transformation 5.2. Variance Stabilizing Transformations5.3. Sources of Bias; 5.4. Normalization; 5.5. Intensity-Dependent Normalization; 5.5.1. Smooth Function Normalization; 5.5.2. Quantile Normalization; 5.5.3. Normalization of Oligonucleotide Arrays; 5.5.4. Normalization of Two-Channel Arrays; 5.5.5. Spatial Normalization; 5.5.6. Stagewise Normalization; 5.6. Judging the Success of a Normalization; 5.7. Outlier Identification; 5.7.1 Nonresistant Rules for Outlier Identification; 5.7.2. Resistant Rules for Outlier Identification; 5.8. Assessing Replicate Array Quality; Exercises; 6. Summarization 6.1. Replication |
| Record Nr. | UNINA-9910829878103321 |
|
Amaratunga Dhammika <1956->
|
||
| Hoboken, NJ, : John Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Exploration and analysis of DNA microarray and protein array data [[electronic resource] /] / Dhammika Amaratunga, Javier Cabrera
| Exploration and analysis of DNA microarray and protein array data [[electronic resource] /] / Dhammika Amaratunga, Javier Cabrera |
| Autore | Amaratunga Dhammika <1956-> |
| Pubbl/distr/stampa | Hoboken, NJ, : John Wiley, c2004 |
| Descrizione fisica | 1 online resource (270 p.) |
| Disciplina |
572.8
572.8636 |
| Altri autori (Persone) | CabreraJavier |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
DNA microarrays - Statistical methods
Protein microarrays - Statistical methods |
| ISBN |
1-282-30744-4
9786612307447 0-470-31712-4 0-470-31796-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Exploration and Analysis of DNA Microarray and Protein A rray Data; Contents; Preface; 1. A Brief Introduction; 1.1. A Note on Exploratory Data Analysis; 1.2. Computing Considerations and Software; 1.3. A Brief Outline of the Book; 2. Genomics Basics; 2.1. Genes; 2.2. DNA; 2.3. Gene Expression; 2.4. Hybridization Assays and Other Laboratory Techniques; 2.5. The Human Genome; 2.6. Genome Variations and Their Consequences; 2.7. Genomics; 2.8. The Role of Genomics in Pharmaceutical Research; 2.9. Proteins; 2.10. Bioinformatics; Supplementary Reading; Exercises; 3. Microarrays
3.1. Types of Microarray Experiments3.1.1. Experiment Type 1: Tissue-Specific Gene Expression; 3.1.2. Experiment Type 2: Developmental Genetics; 3.1.3. Experiment Type 3: Genetic Diseases; 3.1.4. Experiment Type 4: Complex Diseases; 3.1.5. Experiment Type 5: Pharmacological Agents; 3.1.6. Experiment Type 6: Plant Breeding; 3.1.7. Experiment Type 7: Environmental Monitoring; 3.2. A Very Simple Hypothetical Microarray Experiment; 3.3. A Typical Microarray Experiment; 3.3.1. Microarray Preparation; 3.3.2. Sample Preparation; 3.3.3. The Hybridization Step; 3.3.4. Scanning the Microarray 3.3.5. Interpreting the Scanned Image3.4. Multichannel cDNA Microarrays; 3.5. Oligonucleotide Arrays; 3.6. Bead-Based Arrays; 3.7. Confirmation of Microarray Results; Supplementary Reading and Electronic References; Exercises; 4. Processing the Scanned Image; 4.1. Converting the Scanned Image to the Spotted Image; 4.1.1. Gridding; 4.1.2. Segmentation; 4.1.3. Quantification; 4.2. Quality Assessment; 4.2.1. Visualizing the Spotted Image; 4.2.2. Numerical Evaluation of Array Quality; 4.2.3. Spatial Problems; 4.2.4. Spatial Randomness; 4.2.5. Quality Control of Arrays 4.2.6. Assessment of Spot Quality4.3. Adjusting for Background; 4.3.1. Estimating the Background; 4.3.2. Adjusting for the Estimated Background; 4.4. Expression Level Calculation for Two-Channel cDNA Microarrays; 4.5. Expression Level Calculation for Oligonucleotide Arrays; 4.5.1. The Average Difference; 4.5.2. A Weighted Average Difference; 4.5.3. Perfect Matches Only; 4.5.4. Background Adjustment Approach; 4.5.5. Model-Based Approach; 4.5.6. Absent-Present Calls; Supplementary Reading; Exercises; 5. Preprocessing Microarray Data; 5.1. Logarithmic Transformation 5.2. Variance Stabilizing Transformations5.3. Sources of Bias; 5.4. Normalization; 5.5. Intensity-Dependent Normalization; 5.5.1. Smooth Function Normalization; 5.5.2. Quantile Normalization; 5.5.3. Normalization of Oligonucleotide Arrays; 5.5.4. Normalization of Two-Channel Arrays; 5.5.5. Spatial Normalization; 5.5.6. Stagewise Normalization; 5.6. Judging the Success of a Normalization; 5.7. Outlier Identification; 5.7.1 Nonresistant Rules for Outlier Identification; 5.7.2. Resistant Rules for Outlier Identification; 5.8. Assessing Replicate Array Quality; Exercises; 6. Summarization 6.1. Replication |
| Record Nr. | UNINA-9910876590503321 |
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Amaratunga Dhammika <1956->
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| Hoboken, NJ, : John Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Statistics for microarrays [[electronic resource] ] : design, analysis, and inference / / Ernst Wit and John McClure
| Statistics for microarrays [[electronic resource] ] : design, analysis, and inference / / Ernst Wit and John McClure |
| Autore | Wit Ernst |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, USA, : John Wiley & Sons, c2004 |
| Descrizione fisica | 1 online resource (279 p.) |
| Disciplina | 629.04 |
| Altri autori (Persone) | McClureJohn D |
| Soggetto topico | DNA microarrays - Statistical methods |
| ISBN |
1-280-27447-6
9786610274475 0-470-01107-6 0-470-01108-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Preface; 1 Preliminaries; 1.1 Using the R Computing Environment; 1.1.1 Installing smida; 1.1.2 Loading smida; 1.2 Data Sets from Biological Experiments; 1.2.1 Arabidopsis experiment: Anna Amtmann; 1.2.2 Skin cancer experiment: Nighean Barr; 1.2.3 Breast cancer experiment: John Bartlett; 1.2.4 Mammary gland experiment: Gusterson group; 1.2.5 Tuberculosis experiment: BμG@S group; I: Getting Good Data; 2 Set-up of a Microarray Experiment; 2.1 Nucleic Acids: DNA and RNA; 2.2 Simple cDNA Spotted Microarray Experiment; 3 Statistical Design of Microarrays; 3.1 Sources of Variation
3.2 Replication3.3 Design Principles; 3.4 Single-channel Microarray Design; 3.5 Two-channel Microarray Designs; 4 Normalization; 4.1 Image Analysis; 4.2 Introduction to Normalization; 4.3 Normalization for Dual-channel Arrays; 4.4 Normalization of Single-channel Arrays; 5 Quality Assessment; 5.1 Using MIAME in Quality Assessment; 5.2 Comparing Multivariate Data; 5.3 Detecting Data Problems; 5.4 Consequences of Quality Assessment Checks; 6 Microarray Myths: Data; 6.1 Design; 6.2 Normalization; II: Getting Good Answers; 7 Microarray Discoveries; 7.1 Discovering Sample Classes 7.2 Exploratory Supervised Learning7.3 Discovering Gene Clusters; 8 Differential Expression; 8.1 Introduction; 8.2 Classical Hypothesis Testing; 8.3 Bayesian Hypothesis Testing; 9 Predicting Outcomes with Gene Expression Profiles; 9.1 Introduction; 9.2 Curse of Dimensionality: Gene Filtering; 9.3 Predicting Class Memberships; 9.4 Predicting Continuous Responses; 10 Microarray Myths: Inference; 10.1 Differential Expression; 10.2 Prediction and Learning; Bibliography; Index; A; B; C; D; E; F; G; H; I; K; L; M; N; O; P; Q; R; S; T; U; V; W |
| Record Nr. | UNINA-9910145753603321 |
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Wit Ernst
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| Chichester, England ; ; Hoboken, NJ, USA, : John Wiley & Sons, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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