Integrative cluster analysis in bioinformatics /

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Abu Jamous, Basel
Άλλοι συγγραφείς: Fa, Rui, Nandi, Asoke Kumar
Μορφή: Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Chichester, West Sussex, United Kingdom : John Wiley & Sons Inc., [2015]
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Title page; Table of Contents; Preface; List of Symbols; About the Authors; Part One: Introduction; 1 Introduction to Bioinformatics; 1.1 Introduction; 1.2 The "Omics" Era; 1.3 The Scope of Bioinformatics; 1.4 What Do Information Engineers and Biologists Need to Know?; 1.5 Discussion and Summary; References; 2 Computational Methods in Bioinformatics; 2.1 Introduction; 2.2 Machine Learning and Data Mining; 2.3 Optimisation; 2.4 Image Processing: Bioimage Informatics; 2.5 Network Analysis; 2.6 Statistical Analysis; 2.7 Software Tools and Technologies; 2.8 Discussion and Summary; References
  • Part Two: Introduction to Molecular Biology3 The Living Cell; 3.1 Introduction; 3.2 Prokaryotes and Eukaryotes; 3.3 Multicellularity; 3.4 Cell Components; 3.5 Discussion and Summary; References; 4 Central Dogma of Molecular Biology; 4.1 Introduction; 4.2 Central Dogma of Molecular Biology Overview; 4.3 Proteins; 4.4 DNA; 4.5 RNA; 4.6 Genes; 4.7 Transcription and Post-transcriptional Processes; 4.8 Translation and Post-translational Processes; 4.9 Discussion and Summary; References; Part Three: Data Acquisition and Pre-processing; 5 High-throughput Technologies; 5.1 Introduction
  • 5.2 Microarrays5.3 Next-generation Sequencing (NGS); 5.4 ChIP on Microarrays and Sequencing; 5.5 Discussion and Summary; References; 6 Databases, Standards and Annotation; 6.1 Introduction; 6.2 NCBI Databases; 6.3 The EBI Databases; 6.4 Species-specific Databases; 6.5 Discussion and Summary; References; 7 Normalisation; 7.1 Introduction; 7.2 Issues Tackled by Normalisation; 7.3 Normalisation Methods; 7.4 Discussion and Summary; References; 8 Feature Selection; 8.1 Introduction; 8.2 FS and FG
  • Problem Definition; 8.3 Consecutive Ranking; 8.4 Individual Ranking
  • 8.5 Principal Component Analysis8.6 Genetic Algorithms and Genetic Programming; 8.7 Discussion and Summary; References; 9 Differential Expression; 9.1 Introduction; 9.2 Fold Change; 9.3 Statistical Hypothesis Testing
  • Overview; 9.4 Statistical Hypothesis Testing
  • Methods; 9.5 Discussion and Summary; References; Part Four: Clustering Methods; 10 Clustering Forms; 10.1 Introduction; 10.2 Proximity Measures; 10.3 Clustering Families; 10.4 Clusters and Partitions; 10.5 Discussion and Summary; References; 11 Partitional Clustering; 11.1 Introduction; 11.2 k-Means and its Applications
  • 11.3 k-Medoids and its Applications11.4 Discussion and Summary; References; 12 Hierarchical Clustering; 12.1 Introduction; 12.2 Principles; 12.3 Discussion and Summary; References; 13 Fuzzy Clustering; 13.1 Introduction; 13.2 Principles; 13.3 Discussion; References; 14 Neural Network-based Clustering; 14.1 Introduction; 14.2 Algorithms; 14.3 Discussion; References; 15 Mixture Model Clustering; 15.1 Introduction; 15.2 Finite Mixture Models; 15.3 Infinite Mixture Models; 15.4 Discussion; References; 16 Graph Clustering; 16.1 Introduction; 16.2 Basic Definitions; 16.3 Graph Clustering