Automation in proteomics and genomics [[electronic resource] ] : an engineering case-based approach / / [edited by] Gil Alterovitz, Roseann Benson, Marco Ramoni |
Pubbl/distr/stampa | Chichester, West Sussex, U.K. ; ; Hoboken, N.J., : John Wiley, 2009 |
Descrizione fisica | 1 online resource (341 p.) |
Disciplina | 572/.6 |
Altri autori (Persone) |
AlterovitzGil
BensonRoseann RamoniMarco F |
Soggetto topico |
Proteomics - Automation
Genomics - Automation Proteomics - Data processing Genomics - Data processing |
ISBN |
1-282-12328-9
9786612123283 0-470-74119-8 0-470-74117-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | section 1. Fundamentals of molecular and cellular biology -- section 2. Analysis via automation -- section 3. Design via automation -- section 4. Integration. |
Record Nr. | UNINA-9910146137203321 |
Chichester, West Sussex, U.K. ; ; Hoboken, N.J., : John Wiley, 2009 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Automation in proteomics and genomics : an engineering case-based approach / / [edited by] Gil Alterovitz, Roseann Benson, Marco Ramoni |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Chichester, West Sussex, U.K. ; ; Hoboken, N.J., : John Wiley, 2009 |
Descrizione fisica | 1 online resource (341 p.) |
Disciplina | 572/.6 |
Altri autori (Persone) |
AlterovitzGil
BensonRoseann RamoniMarco F |
Soggetto topico |
Proteomics - Automation
Genomics - Automation Proteomics - Data processing Genomics - Data processing |
ISBN |
1-282-12328-9
9786612123283 0-470-74119-8 0-470-74117-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | section 1. Fundamentals of molecular and cellular biology -- section 2. Analysis via automation -- section 3. Design via automation -- section 4. Integration. |
Record Nr. | UNINA-9910825787603321 |
Chichester, West Sussex, U.K. ; ; Hoboken, N.J., : John Wiley, 2009 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Bioinformatics of human proteomics / / editor, Xiandong Wang |
Edizione | [1st ed. 2013.] |
Pubbl/distr/stampa | Dordrecht, : Springer, c2013 |
Descrizione fisica | 1 online resource (393 p.) |
Disciplina | 572.8 |
Altri autori (Persone) | WangXiangdong |
Collana | Translational bioinformatics |
Soggetto topico |
Bioinformatics
Proteomics - Data processing |
ISBN |
1-299-40866-4
94-007-5811-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Clinical Bioinformatics in Human Proteomics Research -- Proteomics defines protein interaction -- Protein Function Microarrays: Design, Use and Bioinformatic Analysis in Cancer Biomarker Discovery and Quantitation -- Proteomics and Cancer Research -- Towards development of novel peptide-based cancer therapeutics: computational design and experimental evaluation -- Advances of proteomic methods -- Clinical and Biomedical Mass Spectrometry – New Frontiers in Drug Developments and Diagnosis -- Disease biomarkers: Modeling MR spectroscopy and clinical applications -- Processing of mass spectrometry data in clinical applications -- Bioinformatics approach for finding target protein in infectious disease -- Identification of network biomarkers for cancer diagnosis -- Software development for quantitative proteomics using stable isotope labeling -- Clinical translation of protein biomarkers integrated with bioinformatics -- Proteomic approaches for urine biomarker discovery in bladder cancer -- Antibody microarray and multiplexing.-Proteomics in Anaesthesia and Intensive Care Medicine. |
Record Nr. | UNINA-9910437839803321 |
Dordrecht, : Springer, c2013 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Computational methods for mass spectrometry proteomics [[electronic resource] /] / Ingvar Eidhammer ... [et al.] |
Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2007 |
Descrizione fisica | 1 online resource (298 p.) |
Disciplina |
572.60285
572/.60285 |
Altri autori (Persone) | EidhammerIngvar |
Soggetto topico |
Proteomics - Data processing
Mass spectrometry - Data processing Bioinformatics |
ISBN |
1-281-32178-8
9786611321789 0-470-72430-7 0-470-72429-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Protein, proteome, and proteomics -- Protein separation : 2D gel electrophoresis -- Protein digestion -- Peptide separation : HPLC -- Fundamentals of mass spectrometry -- Mass spectrometry : MALDI-TOF -- Protein identification and characterization by MS -- Tandem MS or MS/MS analysis -- Fragmentation models -- Identification and characterization by MS/MS -- Spectral comparisons -- Sequential comparison : de novo sequencing -- Database searching for de novo sequences -- Large-scale proteomics -- Quantitative MS-based proteomics -- Peptides to proteins -- Top-down proteomics -- Standards. |
Record Nr. | UNINA-9910144576803321 |
Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2007 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Computational methods for mass spectrometry proteomics [[electronic resource] /] / Ingvar Eidhammer ... [et al.] |
Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2007 |
Descrizione fisica | 1 online resource (298 p.) |
Disciplina |
572.60285
572/.60285 |
Altri autori (Persone) | EidhammerIngvar |
Soggetto topico |
Proteomics - Data processing
Mass spectrometry - Data processing Bioinformatics |
ISBN |
1-281-32178-8
9786611321789 0-470-72430-7 0-470-72429-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Protein, proteome, and proteomics -- Protein separation : 2D gel electrophoresis -- Protein digestion -- Peptide separation : HPLC -- Fundamentals of mass spectrometry -- Mass spectrometry : MALDI-TOF -- Protein identification and characterization by MS -- Tandem MS or MS/MS analysis -- Fragmentation models -- Identification and characterization by MS/MS -- Spectral comparisons -- Sequential comparison : de novo sequencing -- Database searching for de novo sequences -- Large-scale proteomics -- Quantitative MS-based proteomics -- Peptides to proteins -- Top-down proteomics -- Standards. |
Record Nr. | UNINA-9910829976803321 |
Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2007 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Computational methods for mass spectrometry proteomics / / Ingvar Eidhammer ... [et al.] |
Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2007 |
Descrizione fisica | 1 online resource (298 p.) |
Disciplina | 572/.60285 |
Altri autori (Persone) | EidhammerIngvar |
Soggetto topico |
Proteomics - Data processing
Mass spectrometry - Data processing Bioinformatics |
ISBN |
1-281-32178-8
9786611321789 0-470-72430-7 0-470-72429-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Protein, proteome, and proteomics -- Protein separation : 2D gel electrophoresis -- Protein digestion -- Peptide separation : HPLC -- Fundamentals of mass spectrometry -- Mass spectrometry : MALDI-TOF -- Protein identification and characterization by MS -- Tandem MS or MS/MS analysis -- Fragmentation models -- Identification and characterization by MS/MS -- Spectral comparisons -- Sequential comparison : de novo sequencing -- Database searching for de novo sequences -- Large-scale proteomics -- Quantitative MS-based proteomics -- Peptides to proteins -- Top-down proteomics -- Standards. |
Record Nr. | UNINA-9910876973203321 |
Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2007 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Data analysis and visualization in genomics and proteomics [[electronic resource] /] / editors, Francisco Azuaje and Joaquín Dopazo |
Pubbl/distr/stampa | Hoboken, NJ, : John Wiley, c2005 |
Descrizione fisica | 1 online resource (285 p.) |
Disciplina |
372.860285
572.8/6 |
Altri autori (Persone) |
AzuajeFrancisco
DopazoJoaquín |
Soggetto topico |
Genomics - Data processing
Proteomics - Data processing Data mining |
Soggetto genere / forma | Electronic books. |
ISBN |
1-280-27600-2
9786610276004 0-470-09441-9 0-470-09440-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Data Analysis and Visualization in Genomics and Proteomics; Contents; Preface; List of Contributors; SECTION I INTRODUCTION - DATA DIVERSITY AND INTEGRATION; 1 Integrative Data Analysis and Visualization: Introduction to Critical Problems, Goals and Challenges; 1.1 Data Analysis and Visualization: An Integrative Approach; 1.2 Critical Design and Implementation Factors; 1.3 Overview of Contributions; References; 2 Biological Databases: Infrastructure, Content and Integration; 2.1 Introduction; 2.2 Data Integration; 2.3 Review of Molecular Biology Databases; 2.4 Conclusion; References
3 Data and Predictive Model Integration: an Overview of Key Concepts, Problems and Solutions3.1 Integrative Data Analysis and Visualization: Motivation and Approaches; 3.2 Integrating Informational Views and Complexity for Understanding Function; 3.3 Integrating Data Analysis Techniques for Supporting Functional Analysis; 3.4 Final Remarks; References; SECTION II INTEGRATIVE DATA MINING AND VISUALIZATION - EMPHASIS ON COMBINATION OF MULTIPLE DATA TYPES; 4 Applications of Text Mining in Molecular Biology, from Name Recognition to Protein Interaction Maps; 4.1 Introduction 4.2 Introduction to Text Mining and NLP4.3 Databases and Resources for Biomedical Text Mining; 4.4 Text Mining and Protein-Protein Interactions; 4.5 Other Text-Mining Applications in Genomics; 4.6 The Future of NLP in Biomedicine; Acknowledgements; References; 5 Protein Interaction Prediction by Integrating Genomic Features and Protein Interaction Network Analysis; 5.1 Introduction; 5.2 Genomic Features in Protein Interaction Predictions; 5.3 Machine Learning on Protein-Protein Interactions; 5.4 The Missing Value Problem; 5.5 Network Analysis of Protein Interactions; 5.6 Discussion References6 Integration of Genomic and Phenotypic Data; 6.1 Phenotype; 6.2 Forward Genetics and QTL Analysis; 6.3 Reverse Genetics; 6.4 Prediction of Phenotype from Other Sources of Data; 6.5 Integrating Phenotype Data with Systems Biology; 6.6 Integration of Phenotype Data in Databases; 6.7 Conclusions; References; 7 Ontologies and Functional Genomics; 7.1 Information Mining in Genome-Wide Functional Analysis; 7.2 Sources of Information: Free Text Versus Curated Repositories; 7.3 Bio-Ontologies and the Gene Ontology in Functional Genomics 7.4 Using GO to Translate the Results of Functional Genomic Experiments into Biological Knowledge7.5 Statistical Approaches to Test Significant Biological Differences; 7.6 Using FatiGO to Find Significant Functional Associations in Clusters of Genes; 7.7 Other Tools; 7.8 Examples of Functional Analysis of Clusters of Genes; 7.9 Future Prospects; References; 8 The C. elegans Interactome: its Generation and Visualization; 8.1 Introduction; 8.2 The ORFeome: the first step toward the interactome of C. elegans 8.3 Large-Scale High-Throughput Yeast Two-Hybrid Screens to Map the C. elegans Protein-Protein Interaction (Interactome) Network: Technical Aspects |
Record Nr. | UNINA-9910143713103321 |
Hoboken, NJ, : John Wiley, c2005 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Data analysis and visualization in genomics and proteomics [[electronic resource] /] / editors, Francisco Azuaje and Joaquín Dopazo |
Pubbl/distr/stampa | Hoboken, NJ, : John Wiley, c2005 |
Descrizione fisica | 1 online resource (285 p.) |
Disciplina |
372.860285
572.8/6 |
Altri autori (Persone) |
AzuajeFrancisco
DopazoJoaquín |
Soggetto topico |
Genomics - Data processing
Proteomics - Data processing Data mining |
ISBN |
1-280-27600-2
9786610276004 0-470-09441-9 0-470-09440-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Data Analysis and Visualization in Genomics and Proteomics; Contents; Preface; List of Contributors; SECTION I INTRODUCTION - DATA DIVERSITY AND INTEGRATION; 1 Integrative Data Analysis and Visualization: Introduction to Critical Problems, Goals and Challenges; 1.1 Data Analysis and Visualization: An Integrative Approach; 1.2 Critical Design and Implementation Factors; 1.3 Overview of Contributions; References; 2 Biological Databases: Infrastructure, Content and Integration; 2.1 Introduction; 2.2 Data Integration; 2.3 Review of Molecular Biology Databases; 2.4 Conclusion; References
3 Data and Predictive Model Integration: an Overview of Key Concepts, Problems and Solutions3.1 Integrative Data Analysis and Visualization: Motivation and Approaches; 3.2 Integrating Informational Views and Complexity for Understanding Function; 3.3 Integrating Data Analysis Techniques for Supporting Functional Analysis; 3.4 Final Remarks; References; SECTION II INTEGRATIVE DATA MINING AND VISUALIZATION - EMPHASIS ON COMBINATION OF MULTIPLE DATA TYPES; 4 Applications of Text Mining in Molecular Biology, from Name Recognition to Protein Interaction Maps; 4.1 Introduction 4.2 Introduction to Text Mining and NLP4.3 Databases and Resources for Biomedical Text Mining; 4.4 Text Mining and Protein-Protein Interactions; 4.5 Other Text-Mining Applications in Genomics; 4.6 The Future of NLP in Biomedicine; Acknowledgements; References; 5 Protein Interaction Prediction by Integrating Genomic Features and Protein Interaction Network Analysis; 5.1 Introduction; 5.2 Genomic Features in Protein Interaction Predictions; 5.3 Machine Learning on Protein-Protein Interactions; 5.4 The Missing Value Problem; 5.5 Network Analysis of Protein Interactions; 5.6 Discussion References6 Integration of Genomic and Phenotypic Data; 6.1 Phenotype; 6.2 Forward Genetics and QTL Analysis; 6.3 Reverse Genetics; 6.4 Prediction of Phenotype from Other Sources of Data; 6.5 Integrating Phenotype Data with Systems Biology; 6.6 Integration of Phenotype Data in Databases; 6.7 Conclusions; References; 7 Ontologies and Functional Genomics; 7.1 Information Mining in Genome-Wide Functional Analysis; 7.2 Sources of Information: Free Text Versus Curated Repositories; 7.3 Bio-Ontologies and the Gene Ontology in Functional Genomics 7.4 Using GO to Translate the Results of Functional Genomic Experiments into Biological Knowledge7.5 Statistical Approaches to Test Significant Biological Differences; 7.6 Using FatiGO to Find Significant Functional Associations in Clusters of Genes; 7.7 Other Tools; 7.8 Examples of Functional Analysis of Clusters of Genes; 7.9 Future Prospects; References; 8 The C. elegans Interactome: its Generation and Visualization; 8.1 Introduction; 8.2 The ORFeome: the first step toward the interactome of C. elegans 8.3 Large-Scale High-Throughput Yeast Two-Hybrid Screens to Map the C. elegans Protein-Protein Interaction (Interactome) Network: Technical Aspects |
Record Nr. | UNINA-9910830512303321 |
Hoboken, NJ, : John Wiley, c2005 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Data analysis and visualization in genomics and proteomics / / editors, Francisco Azuaje and Joaquin Dopazo |
Pubbl/distr/stampa | Hoboken, NJ, : John Wiley, c2005 |
Descrizione fisica | 1 online resource (285 p.) |
Disciplina | 572.8/6 |
Altri autori (Persone) |
AzuajeFrancisco
DopazoJoaquin |
Soggetto topico |
Genomics - Data processing
Proteomics - Data processing Data mining |
ISBN |
1-280-27600-2
9786610276004 0-470-09441-9 0-470-09440-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Data Analysis and Visualization in Genomics and Proteomics; Contents; Preface; List of Contributors; SECTION I INTRODUCTION - DATA DIVERSITY AND INTEGRATION; 1 Integrative Data Analysis and Visualization: Introduction to Critical Problems, Goals and Challenges; 1.1 Data Analysis and Visualization: An Integrative Approach; 1.2 Critical Design and Implementation Factors; 1.3 Overview of Contributions; References; 2 Biological Databases: Infrastructure, Content and Integration; 2.1 Introduction; 2.2 Data Integration; 2.3 Review of Molecular Biology Databases; 2.4 Conclusion; References
3 Data and Predictive Model Integration: an Overview of Key Concepts, Problems and Solutions3.1 Integrative Data Analysis and Visualization: Motivation and Approaches; 3.2 Integrating Informational Views and Complexity for Understanding Function; 3.3 Integrating Data Analysis Techniques for Supporting Functional Analysis; 3.4 Final Remarks; References; SECTION II INTEGRATIVE DATA MINING AND VISUALIZATION - EMPHASIS ON COMBINATION OF MULTIPLE DATA TYPES; 4 Applications of Text Mining in Molecular Biology, from Name Recognition to Protein Interaction Maps; 4.1 Introduction 4.2 Introduction to Text Mining and NLP4.3 Databases and Resources for Biomedical Text Mining; 4.4 Text Mining and Protein-Protein Interactions; 4.5 Other Text-Mining Applications in Genomics; 4.6 The Future of NLP in Biomedicine; Acknowledgements; References; 5 Protein Interaction Prediction by Integrating Genomic Features and Protein Interaction Network Analysis; 5.1 Introduction; 5.2 Genomic Features in Protein Interaction Predictions; 5.3 Machine Learning on Protein-Protein Interactions; 5.4 The Missing Value Problem; 5.5 Network Analysis of Protein Interactions; 5.6 Discussion References6 Integration of Genomic and Phenotypic Data; 6.1 Phenotype; 6.2 Forward Genetics and QTL Analysis; 6.3 Reverse Genetics; 6.4 Prediction of Phenotype from Other Sources of Data; 6.5 Integrating Phenotype Data with Systems Biology; 6.6 Integration of Phenotype Data in Databases; 6.7 Conclusions; References; 7 Ontologies and Functional Genomics; 7.1 Information Mining in Genome-Wide Functional Analysis; 7.2 Sources of Information: Free Text Versus Curated Repositories; 7.3 Bio-Ontologies and the Gene Ontology in Functional Genomics 7.4 Using GO to Translate the Results of Functional Genomic Experiments into Biological Knowledge7.5 Statistical Approaches to Test Significant Biological Differences; 7.6 Using FatiGO to Find Significant Functional Associations in Clusters of Genes; 7.7 Other Tools; 7.8 Examples of Functional Analysis of Clusters of Genes; 7.9 Future Prospects; References; 8 The C. elegans Interactome: its Generation and Visualization; 8.1 Introduction; 8.2 The ORFeome: the first step toward the interactome of C. elegans 8.3 Large-Scale High-Throughput Yeast Two-Hybrid Screens to Map the C. elegans Protein-Protein Interaction (Interactome) Network: Technical Aspects |
Record Nr. | UNINA-9910877585803321 |
Hoboken, NJ, : John Wiley, c2005 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Data mining for genomics and proteomics : analysis of gene and protein expression data / / Darius M. Dzuida |
Autore | Dziuda Darius M |
Pubbl/distr/stampa | Hoboken, N.J., : Wiley, c2010 |
Descrizione fisica | 1 online resource (348 p.) |
Disciplina | 572.8/6 |
Collana | Wiley Series on Methods and Applications in Data Mining |
Soggetto topico |
Genomics - Data processing
Proteomics - Data processing Data mining |
ISBN |
1-282-70757-4
9786612707575 0-470-59341-5 0-470-59340-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
DATA MINING FOR GENOMICS AND PROTEOMICS; CONTENTS; PREFACE; ACKNOWLEDGMENTS; 1 INTRODUCTION; 1.1 Basic Terminology; 1.1.1 The Central Dogma of Molecular Biology; 1.1.2 Genome; 1.1.3 Proteome; 1.1.4 DNA (Deoxyribonucleic Acid); 1.1.5 RNA (Ribonucleic Acid); 1.1.6 mRNA (messenger RNA); 1.1.7 Genetic Code; 1.1.8 Gene; 1.1.9 Gene Expression and the Gene Expression Level; 1.1.10 Protein; 1.2 Overlapping Areas of Research; 1.2.1 Genomics; 1.2.2 Proteomics; 1.2.3 Bioinformatics; 1.2.4 Transcriptomics and Other -omics . . .; 1.2.5 Data Mining; 2 BASIC ANALYSIS OF GENE EXPRESSION MICROARRAY DATA
2.1 Introduction2.2 Microarray Technology; 2.2.1 Spotted Microarrays; 2.2.2 Affymetrix GeneChip(®) Microarrays; 2.2.3 Bead-Based Microarrays; 2.3 Low-Level Preprocessing of Affymetrix Microarrays; 2.3.1 MAS5; 2.3.2 RMA; 2.3.3 GCRMA; 2.3.4 PLIER; 2.4 Public Repositories of Microarray Data; 2.4.1 Microarray Gene Expression Data Society (MGED) Standards; 2.4.2 Public Databases; 2.4.2.1 Gene Expression Omnibus (GEO); 2.4.2.2 ArrayExpress; 2.5 Gene Expression Matrix; 2.5.1 Elements of Gene Expression Microarray Data Analysis; 2.6 Additional Preprocessing, Quality Assessment, and Filtering 2.6.1 Quality Assessment2.6.2 Filtering; 2.7 Basic Exploratory Data Analysis; 2.7.1 t Test; 2.7.1.1 t Test for Equal Variances; 2.7.1.2 t Test for Unequal Variances; 2.7.2 ANOVA F Test; 2.7.3 SAM t Statistic; 2.7.4 Limma; 2.7.5 Adjustment for Multiple Comparisons; 2.7.5.1 Single-Step Bonferroni Procedure; 2.7.5.2 Single-Step Sidak Procedure; 2.7.5.3 Step-Down Holm Procedure; 2.7.5.4 Step-Up Benjamini and Hochberg Procedure; 2.7.5.5 Permutation Based Multiplicity Adjustment; 2.8 Unsupervised Learning (Taxonomy-Related Analysis); 2.8.1 Cluster Analysis 2.8.1.1 Measures of Similarity or Distance2.8.1.2 K-Means Clustering; 2.8.1.3 Hierarchical Clustering; 2.8.1.4 Two-Way Clustering and Related Methods; 2.8.2 Principal Component Analysis; 2.8.3 Self-Organizing Maps; Exercises; 3 BIOMARKER DISCOVERY AND CLASSIFICATION; 3.1 Overview; 3.1.1 Gene Expression Matrix . . . Again; 3.1.2 Biomarker Discovery; 3.1.3 Classification Systems; 3.1.3.1 Parametric and Nonparametric Learning Algorithms; 3.1.3.2 Terms Associated with Common Assumptions Underlying Parametric Learning Algorithms; 3.1.3.3 Visualization of Classification Results 3.1.4 Validation of the Classification Model3.1.4.1 Reclassification; 3.1.4.2 Leave-One-Out and K-Fold Cross-Validation; 3.1.4.3 External and Internal Cross-Validation; 3.1.4.4 Holdout Method of Validation; 3.1.4.5 Ensemble-Based Validation (Using Out-of-Bag Samples); 3.1.4.6 Validation on an Independent Data Set; 3.1.5 Reporting Validation Results; 3.1.5.1 Binary Classifiers; 3.1.5.2 Multiclass Classifiers; 3.1.6 Identifying Biological Processes Underlying the Class Differentiation; 3.2 Feature Selection; 3.2.1 Introduction; 3.2.2 Univariate Versus Multivariate Approaches 3.2.3 Supervised Versus Unsupervised Methods |
Record Nr. | UNINA-9910140840803321 |
Dziuda Darius M | ||
Hoboken, N.J., : Wiley, c2010 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|