LEADER 04402nam 22007215 450 001 9910298470503321 005 20230810184425.0 010 $a3-319-17780-X 024 7 $a10.1007/978-3-319-17780-9 035 $a(CKB)3710000000412259 035 $a(EBL)2095731 035 $a(SSID)ssj0001501501 035 $a(PQKBManifestationID)11830234 035 $a(PQKBTitleCode)TC0001501501 035 $a(PQKBWorkID)11447122 035 $a(PQKB)10555301 035 $a(DE-He213)978-3-319-17780-9 035 $a(MiAaPQ)EBC2095731 035 $a(PPN)186028083 035 $a(EXLCZ)993710000000412259 100 $a20150509d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aGreat Divergence and Great Convergence $eA Global Perspective /$fby Leonid Grinin, Andrey Korotayev 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (261 p.) 225 1 $aInternational Perspectives on Social Policy, Administration, and Practice,$x2625-6983 300 $aDescription based upon print version of record. 311 $a3-319-17779-6 320 $aIncludes bibliographical references and index. 327 $aIntroduction. And yet the Twain Meet: Great Convergence brings the East closer to the West -- Great Divergence and the Rise of the West -- Great Convergence and the Rise of the Rest -- The Great Convergence and Globalization: How the Former Colo-nies Became the World Economic Locomotives -- Afterword. The Great Convergence and Possible Increase in Global Instability, or the World without an Absolute Leader. 330 $aThis new monograph provides a stimulating new take on hotly contested topics in world modernization and the globalizing economy. It begins by situating what is called the Great Divergence--the social/technological revolution that led European nations to outpace the early dominance of Asia--in historical context over centuries. This is contrasted with an equally powerful Great Convergence, the recent economic and technological expansion taking place in Third World nations and characterized by narrowing inequity among nations. They are seen here as two phases of an inevitable global process, centuries in the making, with the potential for both positive and negative results.   This sophisticated presentation examines:   Why the developing world is growing more rapidly than the developed world. How this development began occurring under the Western world's radar. How former colonies of major powers grew to drive the world's economy. Why so many Western economists have been slow to recognize the Great Convergence. The increasing risk of geopolitical instability. Why the world is likely to find itself without an absolute leader after the end of the American hegemony   A work of rare scope, Great Divergence and Great Convergence gives sociologists, global economists, demographers, and global historians a deeper understanding of the broader movement of social and economic history, combined with a long view of history as it is currently being made; it also offers some thrilling forecasts for global development in the forthcoming decades. 410 0$aInternational Perspectives on Social Policy, Administration, and Practice,$x2625-6983 606 $aInternational economic relations 606 $aDemography 606 $aPopulation 606 $aPopulation$xEconomic aspects 606 $aInternational Economics 606 $aPopulation and Demography 606 $aPopulation Economics 606 $aInternational Political Economy? 615 0$aInternational economic relations. 615 0$aDemography. 615 0$aPopulation. 615 0$aPopulation$xEconomic aspects. 615 14$aInternational Economics. 615 24$aPopulation and Demography. 615 24$aPopulation Economics. 615 24$aInternational Political Economy?. 676 $a304.6 676 $a330 676 $a337 676 $a339.5 700 $aGrinin$b Leonid$4aut$4http://id.loc.gov/vocabulary/relators/aut$0897774 702 $aKorotayev$b Andrey$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910298470503321 996 $aGreat Divergence and Great Convergence$92519730 997 $aUNINA LEADER 05607nam 2200577 a 450 001 9911019314103321 005 20200520144314.0 010 $a9786610556465 010 $a9781280556463 010 $a1280556463 010 $a9780471461180 010 $a0471461180 010 $a9780471227588 010 $a0471227587 035 $a(CKB)1000000000018954 035 $a(EBL)705365 035 $a(SSID)ssj0000290043 035 $a(PQKBManifestationID)11220388 035 $a(PQKBTitleCode)TC0000290043 035 $a(PQKBWorkID)10402854 035 $a(PQKB)10914445 035 $a(MiAaPQ)EBC705365 035 $a(OCoLC)85820194 035 $a(Perlego)2748834 035 $a(EXLCZ)991000000000018954 100 $a20020522d2002 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 12$aA biologist's guide to analysis of DNA microarray data /$fSteen Knudsen 210 $aNew York $cWiley-Interscience$dc2002 215 $a1 online resource (148 p.) 300 $aDescription based upon print version of record. 311 08$a9780471224907 311 08$a0471224901 320 $aIncludes bibliographical references (p. 104-122) and index. 327 $aMachine 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. 330 $aA great introductory book that details reliable approaches to problems met instandard microarray data analyses. It provides examples of establishedapproaches such as cluster analysis, function prediction, and principle component analysis. Discover real examples to illustrate the key concepts of data analysis. Written for those without any advanced background in math, statistics, or computer sciences, this book is essential for anyone interested in harnessing the immense potential of microarrays in biology and medicine. 606 $aDNA microarrays 615 0$aDNA microarrays. 676 $a572.8/636 700 $aKnudsen$b Steen$01837794 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911019314103321 996 $aA biologist's guide to analysis of DNA microarray data$94416625 997 $aUNINA