LEADER 05250nam 2200601 450 001 9910131284203321 005 20200520144314.0 010 $a1-118-90655-1 010 $a1-118-90654-3 010 $a1-118-90656-X 035 $a(CKB)3710000000400816 035 $a(EBL)1895733 035 $a(MiAaPQ)EBC1895733 035 $a(Au-PeEL)EBL1895733 035 $a(CaPaEBR)ebr11050665 035 $a(CaONFJC)MIL779406 035 $a(OCoLC)887606487 035 $a(PPN)19711069X 035 $a(EXLCZ)993710000000400816 100 $a20140815d2015 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aIntegrative cluster analysis in bioinformatics /$fBasel Abu Jamous, Dr Rui Fa, and Prof. Asoke K. Nandi 210 1$aChichester, West Sussex, United Kingdom :$cJohn Wiley & Sons Inc.,$d2015. 215 $a1 online resource (994 p.) 300 $aDescription based upon print version of record. 311 $a1-118-90653-5 320 $aIncludes bibliographical references and index. 327 $aCover; Table of Contents; Title page; 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 327 $aReferencesPart Two: Introduction to Molecular Biology; 3 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 327 $a5.2 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 327 $a8.5 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 327 $a11.3 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 327 $a16.4 Resources 330 $a Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review o 606 $aBioinformatics$xMathematics 606 $aCluster analysis 615 0$aBioinformatics$xMathematics. 615 0$aCluster analysis. 676 $a519.5/3 700 $aAbu Jamous$b Basel$0856994 702 $aFa$b Rui 702 $aNandi$b Asoke Kumar 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910131284203321 996 $aIntegrative cluster analysis in bioinformatics$91913794 997 $aUNINA