top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.

Biblioteca

MARC Lista (tabellare)
A biologist's guide to analysis of DNA microarray data [[electronic resource] /] / Steen Knudsen
A biologist's guide to analysis of DNA microarray data [[electronic resource] /] / Steen Knudsen
Autore Knudsen Steen
Pubbl/distr/stampa New York, : Wiley-Interscience, c2002
Descrizione fisica 1 online resource (148 p.)
Disciplina 572.8/636
572.8636
Soggetto topico DNA microarrays
Soggetto genere / forma Electronic books.
ISBN 1-280-55646-3
9786610556465
0-471-46118-0
0-471-22758-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine generated contents note: Preface xi -- Acknowledgments xiii -- 1 Introduction I -- 1.1 Hybridization 1 -- 1.2 Affymetrix GeneChip Technology 3 -- 1.3 Spotted Arrays 6 -- 1.4 Serial Analysis of Gene Expression (SAGE) 8 -- 1.5 Example: Affymetrix vs. Spotted Arrays 9 -- 1.6 Summary 11 -- 1.7 Further Reading 13 -- 2 Overview of Data Analysis 15 -- 3 Basic Data Analysis 17 -- 3.1 Absolute Measurements 17 -- 3.2 Scaling 18 -- 3.2.1 Example: Linear and Nonlinear Scaling 20 -- 3.3 Detection of Outliers 20 -- 3.4 Fold Change 21 -- 3.5 Significance 22 -- 3.5.1 Nonparametric Tests 24 -- 3.5.2 Correction for Multiple Testing 24 -- 3.5.3 Example I: t-Test and ANOVA 25 -- 3.5.4 Example II: Number of Replicates 26 -- 3.6 Summary 28 -- 3.7 Further Reading 29 -- 4 Visualization by Reduction of Dimensionality 33 -- 4.1 Principal Component Analysis 33 -- 4.2 Example 1: PCA on Small Data Matrix 35 -- 4.3 Example 2: PCA on Real Data 37 -- 4.4 Summary 37 -- 4.5 Further Reading 39 -- 5 Cluster Analysis 41 -- 5.1 Hierarchical Clustering 41 -- 5.2 K-means Clustering 43 -- 5.3 Self-Organizing Maps 44 -- 5.4 Distance Measures 45 -- 5.4.1 Example: Comparison of Distance Measures 47 -- 5.5 Normalization 49 -- 5.6 Visualization of Clusters 50 -- 5.6.1 Example: Visualization of Gene Clusters in -- Bladder Cancer 50 -- 5.7 Summary 50 -- 5.8 Further Reading 52 -- 6 Beyond Cluster Analysis 55 -- 6.1 Function Prediction 55 -- 6.2 Discovery of Regulatory Elements in Promoter -- Regions 56 -- 6.2.1 Example 1: Discovery of Proteasomal Element 57 -- 6.2.2 Example 2: Rediscovery of Mlu Cell Cycle -- Box (MCB) 57 -- 6.3 Integration of data 58 -- 6.4 Summary 59 -- 6.5 Further Reading 59 -- 7 Reverse Engineering of Regulatory Networks 63 -- 7.1 The Time-Series Approach 63 -- 7.2 The Steady-State Approach 64 -- 7.3 Limitations of Network Modeling 65 -- 7.4 Example 1: Steady-State Model 65 -- 7.5 Example 2: Steady-State Model on Real Data 66 -- 7.6 Example 3: Steady-State Model on Real Data 68 -- 7.7 Example 4: Linear Time-Series Model 68 -- 7.8 Further Reading 71 -- 8 Molecular Classifiers 75 -- 8.1 Classification Schemes 76 -- 8.1.1 Nearest Neighbor 76 -- 8.1.2 Neural Networks 76 -- 8.1.3 Support Vector Machine 76 -- 8.2 Example I: Classification of Cancer Subtypes 77 -- 8.3 Example II: Classification of Cancer Subtypes 78 -- 8.4 Summary 79 -- 8.5 Further Reading 79 -- 9 Selection of Genes for Spotting on Arrays 81 -- 9.1 Gene Finding 82 -- 9.2 Selection of Regions Within Genes 82 -- 9.3 Selection of Primers for PCR 83 -- 9.4 Selection of Unique Oligomer Probes 83 -- 9.4.1 Example: Finding PCR Primers for Gene -- AF105374 83 -- 9.5 Experimental Design 84 -- 9.6 Further Reading 84 -- 10 Limitations of Expression Analysis 87 -- 10.1 Relative VersusAbsoluteRNA Quantification 88 -- 10.2 Further Reading 88 -- 11 Genotyping Chips 91 -- 11.1 Example: NeuralNetworksfor GeneChipprediction 91 -- 11.2 Further Reading 93 -- 12 Software Issues and Data Formats 95 -- 12.1 Standardization Efforts 96 -- 12.2 Standard File Format 97 -- 12.2.1 Example: Small Scripts in Awk 97 -- 12.3 Software for Clustering 98 -- 12.3.1 Example: Clustering with ClustArray 99 -- 12.4 Software for Statistical Analysis 99 -- 12.4.1 Example: StatisticalAnalysis with R 99 -- 12.4.2 The affyR Software Package 103 -- 12.4.3 Commercial Statistics Packages 103 -- 12.5 Summary 103 -- 12.6 Further Reading 104 -- 13 Commercial Software Packages 105 -- 14 Bibliography 109 -- Index 123.
Record Nr. UNINA-9910146082503321
Knudsen Steen  
New York, : Wiley-Interscience, c2002
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
A biologist's guide to analysis of DNA microarray data [[electronic resource] /] / Steen Knudsen
A biologist's guide to analysis of DNA microarray data [[electronic resource] /] / Steen Knudsen
Autore Knudsen Steen
Pubbl/distr/stampa New York, : Wiley-Interscience, c2002
Descrizione fisica 1 online resource (148 p.)
Disciplina 572.8/636
572.8636
Soggetto topico DNA microarrays
ISBN 1-280-55646-3
9786610556465
0-471-46118-0
0-471-22758-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine generated contents note: Preface xi -- Acknowledgments xiii -- 1 Introduction I -- 1.1 Hybridization 1 -- 1.2 Affymetrix GeneChip Technology 3 -- 1.3 Spotted Arrays 6 -- 1.4 Serial Analysis of Gene Expression (SAGE) 8 -- 1.5 Example: Affymetrix vs. Spotted Arrays 9 -- 1.6 Summary 11 -- 1.7 Further Reading 13 -- 2 Overview of Data Analysis 15 -- 3 Basic Data Analysis 17 -- 3.1 Absolute Measurements 17 -- 3.2 Scaling 18 -- 3.2.1 Example: Linear and Nonlinear Scaling 20 -- 3.3 Detection of Outliers 20 -- 3.4 Fold Change 21 -- 3.5 Significance 22 -- 3.5.1 Nonparametric Tests 24 -- 3.5.2 Correction for Multiple Testing 24 -- 3.5.3 Example I: t-Test and ANOVA 25 -- 3.5.4 Example II: Number of Replicates 26 -- 3.6 Summary 28 -- 3.7 Further Reading 29 -- 4 Visualization by Reduction of Dimensionality 33 -- 4.1 Principal Component Analysis 33 -- 4.2 Example 1: PCA on Small Data Matrix 35 -- 4.3 Example 2: PCA on Real Data 37 -- 4.4 Summary 37 -- 4.5 Further Reading 39 -- 5 Cluster Analysis 41 -- 5.1 Hierarchical Clustering 41 -- 5.2 K-means Clustering 43 -- 5.3 Self-Organizing Maps 44 -- 5.4 Distance Measures 45 -- 5.4.1 Example: Comparison of Distance Measures 47 -- 5.5 Normalization 49 -- 5.6 Visualization of Clusters 50 -- 5.6.1 Example: Visualization of Gene Clusters in -- Bladder Cancer 50 -- 5.7 Summary 50 -- 5.8 Further Reading 52 -- 6 Beyond Cluster Analysis 55 -- 6.1 Function Prediction 55 -- 6.2 Discovery of Regulatory Elements in Promoter -- Regions 56 -- 6.2.1 Example 1: Discovery of Proteasomal Element 57 -- 6.2.2 Example 2: Rediscovery of Mlu Cell Cycle -- Box (MCB) 57 -- 6.3 Integration of data 58 -- 6.4 Summary 59 -- 6.5 Further Reading 59 -- 7 Reverse Engineering of Regulatory Networks 63 -- 7.1 The Time-Series Approach 63 -- 7.2 The Steady-State Approach 64 -- 7.3 Limitations of Network Modeling 65 -- 7.4 Example 1: Steady-State Model 65 -- 7.5 Example 2: Steady-State Model on Real Data 66 -- 7.6 Example 3: Steady-State Model on Real Data 68 -- 7.7 Example 4: Linear Time-Series Model 68 -- 7.8 Further Reading 71 -- 8 Molecular Classifiers 75 -- 8.1 Classification Schemes 76 -- 8.1.1 Nearest Neighbor 76 -- 8.1.2 Neural Networks 76 -- 8.1.3 Support Vector Machine 76 -- 8.2 Example I: Classification of Cancer Subtypes 77 -- 8.3 Example II: Classification of Cancer Subtypes 78 -- 8.4 Summary 79 -- 8.5 Further Reading 79 -- 9 Selection of Genes for Spotting on Arrays 81 -- 9.1 Gene Finding 82 -- 9.2 Selection of Regions Within Genes 82 -- 9.3 Selection of Primers for PCR 83 -- 9.4 Selection of Unique Oligomer Probes 83 -- 9.4.1 Example: Finding PCR Primers for Gene -- AF105374 83 -- 9.5 Experimental Design 84 -- 9.6 Further Reading 84 -- 10 Limitations of Expression Analysis 87 -- 10.1 Relative VersusAbsoluteRNA Quantification 88 -- 10.2 Further Reading 88 -- 11 Genotyping Chips 91 -- 11.1 Example: NeuralNetworksfor GeneChipprediction 91 -- 11.2 Further Reading 93 -- 12 Software Issues and Data Formats 95 -- 12.1 Standardization Efforts 96 -- 12.2 Standard File Format 97 -- 12.2.1 Example: Small Scripts in Awk 97 -- 12.3 Software for Clustering 98 -- 12.3.1 Example: Clustering with ClustArray 99 -- 12.4 Software for Statistical Analysis 99 -- 12.4.1 Example: StatisticalAnalysis with R 99 -- 12.4.2 The affyR Software Package 103 -- 12.4.3 Commercial Statistics Packages 103 -- 12.5 Summary 103 -- 12.6 Further Reading 104 -- 13 Commercial Software Packages 105 -- 14 Bibliography 109 -- Index 123.
Record Nr. UNINA-9910830115503321
Knudsen Steen  
New York, : Wiley-Interscience, c2002
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
A biologist's guide to analysis of DNA microarray data / / Steen Knudsen
A biologist's guide to analysis of DNA microarray data / / Steen Knudsen
Autore Knudsen Steen
Pubbl/distr/stampa New York, : Wiley-Interscience, c2002
Descrizione fisica 1 online resource (148 p.)
Disciplina 572.8/636
Soggetto topico DNA microarrays
ISBN 1-280-55646-3
9786610556465
0-471-46118-0
0-471-22758-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine generated contents note: Preface xi -- Acknowledgments xiii -- 1 Introduction I -- 1.1 Hybridization 1 -- 1.2 Affymetrix GeneChip Technology 3 -- 1.3 Spotted Arrays 6 -- 1.4 Serial Analysis of Gene Expression (SAGE) 8 -- 1.5 Example: Affymetrix vs. Spotted Arrays 9 -- 1.6 Summary 11 -- 1.7 Further Reading 13 -- 2 Overview of Data Analysis 15 -- 3 Basic Data Analysis 17 -- 3.1 Absolute Measurements 17 -- 3.2 Scaling 18 -- 3.2.1 Example: Linear and Nonlinear Scaling 20 -- 3.3 Detection of Outliers 20 -- 3.4 Fold Change 21 -- 3.5 Significance 22 -- 3.5.1 Nonparametric Tests 24 -- 3.5.2 Correction for Multiple Testing 24 -- 3.5.3 Example I: t-Test and ANOVA 25 -- 3.5.4 Example II: Number of Replicates 26 -- 3.6 Summary 28 -- 3.7 Further Reading 29 -- 4 Visualization by Reduction of Dimensionality 33 -- 4.1 Principal Component Analysis 33 -- 4.2 Example 1: PCA on Small Data Matrix 35 -- 4.3 Example 2: PCA on Real Data 37 -- 4.4 Summary 37 -- 4.5 Further Reading 39 -- 5 Cluster Analysis 41 -- 5.1 Hierarchical Clustering 41 -- 5.2 K-means Clustering 43 -- 5.3 Self-Organizing Maps 44 -- 5.4 Distance Measures 45 -- 5.4.1 Example: Comparison of Distance Measures 47 -- 5.5 Normalization 49 -- 5.6 Visualization of Clusters 50 -- 5.6.1 Example: Visualization of Gene Clusters in -- Bladder Cancer 50 -- 5.7 Summary 50 -- 5.8 Further Reading 52 -- 6 Beyond Cluster Analysis 55 -- 6.1 Function Prediction 55 -- 6.2 Discovery of Regulatory Elements in Promoter -- Regions 56 -- 6.2.1 Example 1: Discovery of Proteasomal Element 57 -- 6.2.2 Example 2: Rediscovery of Mlu Cell Cycle -- Box (MCB) 57 -- 6.3 Integration of data 58 -- 6.4 Summary 59 -- 6.5 Further Reading 59 -- 7 Reverse Engineering of Regulatory Networks 63 -- 7.1 The Time-Series Approach 63 -- 7.2 The Steady-State Approach 64 -- 7.3 Limitations of Network Modeling 65 -- 7.4 Example 1: Steady-State Model 65 -- 7.5 Example 2: Steady-State Model on Real Data 66 -- 7.6 Example 3: Steady-State Model on Real Data 68 -- 7.7 Example 4: Linear Time-Series Model 68 -- 7.8 Further Reading 71 -- 8 Molecular Classifiers 75 -- 8.1 Classification Schemes 76 -- 8.1.1 Nearest Neighbor 76 -- 8.1.2 Neural Networks 76 -- 8.1.3 Support Vector Machine 76 -- 8.2 Example I: Classification of Cancer Subtypes 77 -- 8.3 Example II: Classification of Cancer Subtypes 78 -- 8.4 Summary 79 -- 8.5 Further Reading 79 -- 9 Selection of Genes for Spotting on Arrays 81 -- 9.1 Gene Finding 82 -- 9.2 Selection of Regions Within Genes 82 -- 9.3 Selection of Primers for PCR 83 -- 9.4 Selection of Unique Oligomer Probes 83 -- 9.4.1 Example: Finding PCR Primers for Gene -- AF105374 83 -- 9.5 Experimental Design 84 -- 9.6 Further Reading 84 -- 10 Limitations of Expression Analysis 87 -- 10.1 Relative VersusAbsoluteRNA Quantification 88 -- 10.2 Further Reading 88 -- 11 Genotyping Chips 91 -- 11.1 Example: NeuralNetworksfor GeneChipprediction 91 -- 11.2 Further Reading 93 -- 12 Software Issues and Data Formats 95 -- 12.1 Standardization Efforts 96 -- 12.2 Standard File Format 97 -- 12.2.1 Example: Small Scripts in Awk 97 -- 12.3 Software for Clustering 98 -- 12.3.1 Example: Clustering with ClustArray 99 -- 12.4 Software for Statistical Analysis 99 -- 12.4.1 Example: StatisticalAnalysis with R 99 -- 12.4.2 The affyR Software Package 103 -- 12.4.3 Commercial Statistics Packages 103 -- 12.5 Summary 103 -- 12.6 Further Reading 104 -- 13 Commercial Software Packages 105 -- 14 Bibliography 109 -- Index 123.
Record Nr. UNINA-9910876809203321
Knudsen Steen  
New York, : Wiley-Interscience, c2002
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Cancer diagnostics with DNA microarrays [[electronic resource] /] / Steen Knudsen
Cancer diagnostics with DNA microarrays [[electronic resource] /] / Steen Knudsen
Autore Knudsen Steen
Pubbl/distr/stampa Hoboken, N.J., : Wiley-Liss, c2006
Descrizione fisica 1 online resource (213 p.)
Disciplina 616.994075
Soggetto topico DNA microarrays - Diagnostic use
Cancer - Diagnosis
Soggetto genere / forma Electronic books.
ISBN 1-280-55153-4
9786610551538
0-470-04110-2
0-470-04109-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction to DNA microarray technology -- Image analysis -- Basic data analysis -- Visualization by reduction of dimensionality -- Cluster analysis -- Molecular classifiers for cancer -- Survival analysis -- Meta-analysis -- The design of probes for arrays -- Software issues and data formats -- Breast cancer -- Leukemia -- Lymphoma -- Lung cancer -- Bladder cancer -- Colon cancer -- Ovarian cancer -- Prostate cancer -- Melanoma -- Brain tumors -- Organ or tissue specific classification -- Sample collection and stability.
Record Nr. UNINA-9910143418003321
Knudsen Steen  
Hoboken, N.J., : Wiley-Liss, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Cancer diagnostics with DNA microarrays / / Steen Knudsen
Cancer diagnostics with DNA microarrays / / Steen Knudsen
Autore Knudsen Steen
Pubbl/distr/stampa Hoboken, N.J., : Wiley-Liss, c2006
Descrizione fisica 1 online resource (213 p.)
Disciplina 616.99/4075
Soggetto topico DNA microarrays - Diagnostic use
Cancer - Diagnosis
ISBN 1-280-55153-4
9786610551538
0-470-04110-2
0-470-04109-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction to DNA microarray technology -- Image analysis -- Basic data analysis -- Visualization by reduction of dimensionality -- Cluster analysis -- Molecular classifiers for cancer -- Survival analysis -- Meta-analysis -- The design of probes for arrays -- Software issues and data formats -- Breast cancer -- Leukemia -- Lymphoma -- Lung cancer -- Bladder cancer -- Colon cancer -- Ovarian cancer -- Prostate cancer -- Melanoma -- Brain tumors -- Organ or tissue specific classification -- Sample collection and stability.
Record Nr. UNINA-9910877039403321
Knudsen Steen  
Hoboken, N.J., : Wiley-Liss, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Guide to analysis of DNA microarray data [[electronic resource] /] / Steen Knudsen
Guide to analysis of DNA microarray data [[electronic resource] /] / Steen Knudsen
Autore Knudsen Steen
Edizione [2nd ed.]
Pubbl/distr/stampa Hoboken, N.J., : Wiley-Liss, c2004
Descrizione fisica 1 online resource (194 p.)
Disciplina 572.86
572.8636
Altri autori (Persone) KnudsenSteen
Soggetto topico DNA microarrays
Soggetto genere / forma Electronic books.
ISBN 1-280-25320-7
9786610253203
0-471-67026-X
0-471-67027-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Guide to ANALYSIS OF DNA MICROARRAY DATA; Contents; Preface; Acknowledgments; 1 Introduction to DNA Microarray Technology; 1.1 Hybridization; 1.2 Gold Rush?; 1.3 The Technology Behind DNA Microarrays; 1.3.1 Affymetrix GeneChip Technology; 1.3.2 Spotted Arrays; 1.3.3 Digital Micromirror Arrays; 1.3.4 Inkjet Arrays; 1.3.5 Bead Arrays; 1.3.6 Serial Analysis of Gene Expression (SAGE); 1.4 Parallel Sequencing on Microbead Arrays; 1.4.1 Emerging Technologies; 1.5 Example: Affymetrix vs. Spotted Arrays; 1.6 Summary; 1.7 Further Reading; 2 Overview of Data Analysis; 3 Image Analysis; 3.1 Gridding
3.2 Segmentation3.3 Intensity Extraction; 3.4 Background Correction; 3.5 Software; 3.5.1 Free Software for Array Image Analysis; 3.5.2 Commercial Software for Array Image Analysis; 3.6 Summary; 3.7 Further Reading; 4 Basic Data Analysis; 4.1 Normalization; 4.1.1 One or More Genes Assumed Expressed at Constant Rate; 4.1.2 Sum of Genes is Assumed Constant; 4.1.3 Subset of Genes is Assumed Constant; 4.1.4 Majority of Genes Assumed Constant; 4.1.5 Spike Controls; 4.2 Dye Bias, Spatial Bias, Print Tip Bias; 4.3 Expression Indices; 4.3.1 Average Difference; 4.3.2 Signal
4.3.3 Model-Based Expression Index4.3.4 Robust Multiarray Average; 4.3.5 Position Dependent Nearest Neighbor Model; 4.4 Detection of Outliers; 4.5 Fold Change; 4.6 Significance; 4.6.1 Multiple Conditions; 4.6.2 Nonparametric Tests; 4.6.3 Correction for Multiple Testing; 4.6.4 Example I: t-Test and ANOVA; 4.6.5 Example II: Number of Replicates; 4.7 Mixed Cell Populations; 4.8 Summary; 4.9 Further Reading; 5 Visualization by Reduction of Dimensionality; 5.1 Principal Component Analysis; 5.2 Example 1: PCA on Small Data Matrix; 5.3 Example 2: PCA on Real Data; 5.4 Summary; 5.5 Further Reading
6 Cluster Analysis6.1 Hierarchical Clustering; 6.2 K-means Clustering; 6.3 Self-organizing Maps; 6.4 Distance Measures; 6.4.1 Example: Comparison of Distance Measures; 6.5 Time-Series Analysis; 6.6 Gene Normalization; 6.7 Visualization of Clusters; 6.7.1 Example: Visualization of Gene Clusters in Bladder Cancer; 6.8 Summary; 6.9 Further Reading; 7 Beyond Cluster Analysis; 7.1 Function Prediction; 7.2 Discovery of Regulatory Elements in Promoter Regions; 7.2.1 Example 1: Discovery of Proteasomal Element; 7.2.2 Example 2: Rediscovery of Mlu Cell Cycle Box (MCB); 7.3 Summary; 7.4 Further Reading
8 Automated Analysis, Integrated Analysis, and Systems Biology8.1 Integrated Analysis; 8.2 Systems Biology; 8.3 Further Reading; 9 Reverse Engineering of Regulatory Networks; 9.1 The Time-Series Approach; 9.2 The Steady-State Approach; 9.3 Limitations of Network Modeling; 9.4 Example 1: Steady-State Model; 9.5 Example 2: Steady-State Model on Bacillus Data; 9.6 Example 3: Linear Time-Series Model; 9.7 Further Reading; 10 Molecular Classifiers; 10.1 Feature Selection; 10.2 Validation; 10.3 Classification Schemes; 10.3.1 Nearest Neighbor; 10.3.2 Nearest Centroid; 10.3.3 Neural Networks
10.3.4 Support Vector Machine
Altri titoli varianti Analysis of DNA microarray data
Record Nr. UNINA-9910146073503321
Knudsen Steen  
Hoboken, N.J., : Wiley-Liss, c2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Guide to analysis of DNA microarray data [[electronic resource] /] / Steen Knudsen
Guide to analysis of DNA microarray data [[electronic resource] /] / Steen Knudsen
Autore Knudsen Steen
Edizione [2nd ed.]
Pubbl/distr/stampa Hoboken, N.J., : Wiley-Liss, c2004
Descrizione fisica 1 online resource (194 p.)
Disciplina 572.86
572.8636
Altri autori (Persone) KnudsenSteen
Soggetto topico DNA microarrays
ISBN 1-280-25320-7
9786610253203
0-471-67026-X
0-471-67027-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Guide to ANALYSIS OF DNA MICROARRAY DATA; Contents; Preface; Acknowledgments; 1 Introduction to DNA Microarray Technology; 1.1 Hybridization; 1.2 Gold Rush?; 1.3 The Technology Behind DNA Microarrays; 1.3.1 Affymetrix GeneChip Technology; 1.3.2 Spotted Arrays; 1.3.3 Digital Micromirror Arrays; 1.3.4 Inkjet Arrays; 1.3.5 Bead Arrays; 1.3.6 Serial Analysis of Gene Expression (SAGE); 1.4 Parallel Sequencing on Microbead Arrays; 1.4.1 Emerging Technologies; 1.5 Example: Affymetrix vs. Spotted Arrays; 1.6 Summary; 1.7 Further Reading; 2 Overview of Data Analysis; 3 Image Analysis; 3.1 Gridding
3.2 Segmentation3.3 Intensity Extraction; 3.4 Background Correction; 3.5 Software; 3.5.1 Free Software for Array Image Analysis; 3.5.2 Commercial Software for Array Image Analysis; 3.6 Summary; 3.7 Further Reading; 4 Basic Data Analysis; 4.1 Normalization; 4.1.1 One or More Genes Assumed Expressed at Constant Rate; 4.1.2 Sum of Genes is Assumed Constant; 4.1.3 Subset of Genes is Assumed Constant; 4.1.4 Majority of Genes Assumed Constant; 4.1.5 Spike Controls; 4.2 Dye Bias, Spatial Bias, Print Tip Bias; 4.3 Expression Indices; 4.3.1 Average Difference; 4.3.2 Signal
4.3.3 Model-Based Expression Index4.3.4 Robust Multiarray Average; 4.3.5 Position Dependent Nearest Neighbor Model; 4.4 Detection of Outliers; 4.5 Fold Change; 4.6 Significance; 4.6.1 Multiple Conditions; 4.6.2 Nonparametric Tests; 4.6.3 Correction for Multiple Testing; 4.6.4 Example I: t-Test and ANOVA; 4.6.5 Example II: Number of Replicates; 4.7 Mixed Cell Populations; 4.8 Summary; 4.9 Further Reading; 5 Visualization by Reduction of Dimensionality; 5.1 Principal Component Analysis; 5.2 Example 1: PCA on Small Data Matrix; 5.3 Example 2: PCA on Real Data; 5.4 Summary; 5.5 Further Reading
6 Cluster Analysis6.1 Hierarchical Clustering; 6.2 K-means Clustering; 6.3 Self-organizing Maps; 6.4 Distance Measures; 6.4.1 Example: Comparison of Distance Measures; 6.5 Time-Series Analysis; 6.6 Gene Normalization; 6.7 Visualization of Clusters; 6.7.1 Example: Visualization of Gene Clusters in Bladder Cancer; 6.8 Summary; 6.9 Further Reading; 7 Beyond Cluster Analysis; 7.1 Function Prediction; 7.2 Discovery of Regulatory Elements in Promoter Regions; 7.2.1 Example 1: Discovery of Proteasomal Element; 7.2.2 Example 2: Rediscovery of Mlu Cell Cycle Box (MCB); 7.3 Summary; 7.4 Further Reading
8 Automated Analysis, Integrated Analysis, and Systems Biology8.1 Integrated Analysis; 8.2 Systems Biology; 8.3 Further Reading; 9 Reverse Engineering of Regulatory Networks; 9.1 The Time-Series Approach; 9.2 The Steady-State Approach; 9.3 Limitations of Network Modeling; 9.4 Example 1: Steady-State Model; 9.5 Example 2: Steady-State Model on Bacillus Data; 9.6 Example 3: Linear Time-Series Model; 9.7 Further Reading; 10 Molecular Classifiers; 10.1 Feature Selection; 10.2 Validation; 10.3 Classification Schemes; 10.3.1 Nearest Neighbor; 10.3.2 Nearest Centroid; 10.3.3 Neural Networks
10.3.4 Support Vector Machine
Altri titoli varianti Analysis of DNA microarray data
Record Nr. UNINA-9910830332603321
Knudsen Steen  
Hoboken, N.J., : Wiley-Liss, c2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Guide to analysis of DNA microarray data / / Steen Knudsen
Guide to analysis of DNA microarray data / / Steen Knudsen
Autore Knudsen Steen
Edizione [2nd ed.]
Pubbl/distr/stampa Hoboken, N.J., : Wiley-Liss, c2004
Descrizione fisica 1 online resource (194 p.)
Disciplina 572.8/636
Altri autori (Persone) KnudsenSteen
Soggetto topico DNA microarrays
ISBN 1-280-25320-7
9786610253203
0-471-67026-X
0-471-67027-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Guide to ANALYSIS OF DNA MICROARRAY DATA; Contents; Preface; Acknowledgments; 1 Introduction to DNA Microarray Technology; 1.1 Hybridization; 1.2 Gold Rush?; 1.3 The Technology Behind DNA Microarrays; 1.3.1 Affymetrix GeneChip Technology; 1.3.2 Spotted Arrays; 1.3.3 Digital Micromirror Arrays; 1.3.4 Inkjet Arrays; 1.3.5 Bead Arrays; 1.3.6 Serial Analysis of Gene Expression (SAGE); 1.4 Parallel Sequencing on Microbead Arrays; 1.4.1 Emerging Technologies; 1.5 Example: Affymetrix vs. Spotted Arrays; 1.6 Summary; 1.7 Further Reading; 2 Overview of Data Analysis; 3 Image Analysis; 3.1 Gridding
3.2 Segmentation3.3 Intensity Extraction; 3.4 Background Correction; 3.5 Software; 3.5.1 Free Software for Array Image Analysis; 3.5.2 Commercial Software for Array Image Analysis; 3.6 Summary; 3.7 Further Reading; 4 Basic Data Analysis; 4.1 Normalization; 4.1.1 One or More Genes Assumed Expressed at Constant Rate; 4.1.2 Sum of Genes is Assumed Constant; 4.1.3 Subset of Genes is Assumed Constant; 4.1.4 Majority of Genes Assumed Constant; 4.1.5 Spike Controls; 4.2 Dye Bias, Spatial Bias, Print Tip Bias; 4.3 Expression Indices; 4.3.1 Average Difference; 4.3.2 Signal
4.3.3 Model-Based Expression Index4.3.4 Robust Multiarray Average; 4.3.5 Position Dependent Nearest Neighbor Model; 4.4 Detection of Outliers; 4.5 Fold Change; 4.6 Significance; 4.6.1 Multiple Conditions; 4.6.2 Nonparametric Tests; 4.6.3 Correction for Multiple Testing; 4.6.4 Example I: t-Test and ANOVA; 4.6.5 Example II: Number of Replicates; 4.7 Mixed Cell Populations; 4.8 Summary; 4.9 Further Reading; 5 Visualization by Reduction of Dimensionality; 5.1 Principal Component Analysis; 5.2 Example 1: PCA on Small Data Matrix; 5.3 Example 2: PCA on Real Data; 5.4 Summary; 5.5 Further Reading
6 Cluster Analysis6.1 Hierarchical Clustering; 6.2 K-means Clustering; 6.3 Self-organizing Maps; 6.4 Distance Measures; 6.4.1 Example: Comparison of Distance Measures; 6.5 Time-Series Analysis; 6.6 Gene Normalization; 6.7 Visualization of Clusters; 6.7.1 Example: Visualization of Gene Clusters in Bladder Cancer; 6.8 Summary; 6.9 Further Reading; 7 Beyond Cluster Analysis; 7.1 Function Prediction; 7.2 Discovery of Regulatory Elements in Promoter Regions; 7.2.1 Example 1: Discovery of Proteasomal Element; 7.2.2 Example 2: Rediscovery of Mlu Cell Cycle Box (MCB); 7.3 Summary; 7.4 Further Reading
8 Automated Analysis, Integrated Analysis, and Systems Biology8.1 Integrated Analysis; 8.2 Systems Biology; 8.3 Further Reading; 9 Reverse Engineering of Regulatory Networks; 9.1 The Time-Series Approach; 9.2 The Steady-State Approach; 9.3 Limitations of Network Modeling; 9.4 Example 1: Steady-State Model; 9.5 Example 2: Steady-State Model on Bacillus Data; 9.6 Example 3: Linear Time-Series Model; 9.7 Further Reading; 10 Molecular Classifiers; 10.1 Feature Selection; 10.2 Validation; 10.3 Classification Schemes; 10.3.1 Nearest Neighbor; 10.3.2 Nearest Centroid; 10.3.3 Neural Networks
10.3.4 Support Vector Machine
Altri titoli varianti Analysis of DNA microarray data
Record Nr. UNINA-9910877020803321
Knudsen Steen  
Hoboken, N.J., : Wiley-Liss, c2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui