LEADER 05279nam 2200625 a 450 001 9910876527903321 005 20200520144314.0 010 $a1-282-68778-6 010 $a9786612687785 010 $a3-527-63033-3 010 $a3-527-63034-1 035 $a(CKB)2670000000019018 035 $a(EBL)530456 035 $a(OCoLC)630542410 035 $a(SSID)ssj0000422933 035 $a(PQKBManifestationID)11277523 035 $a(PQKBTitleCode)TC0000422933 035 $a(PQKBWorkID)10432779 035 $a(PQKB)10258035 035 $a(MiAaPQ)EBC530456 035 $a(EXLCZ)992670000000019018 100 $a20100614d2010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aMedical biostatistics for complex diseases /$fedited by Frank Emmert-Streib and Matthias Dehmer 210 $aWeimheim $cWiley-VCH$d2010 215 $a1 online resource (413 p.) 300 $aDescription based upon print version of record. 311 $a3-527-32585-9 320 $aIncludes bibliographical references and index. 327 $aMedical Biostatistics for Complex Diseases; Foreword; Contents; Preface; List of Contributors; Part One: General Biological and Statistical Basics; 1 The Biology of MYC in Health and Disease: A High Altitude View; 1.1 Introduction; 1.2 MYC and Normal Physiology; 1.3 Regulation of Transcription and Gene Expression; 1.4 Metabolism; 1.5 Cell-Cycle Regulation and Differentiation; 1.6 Protein Synthesis; 1.7 Cell Adhesion; 1.8 Apoptosis; 1.9 MicroRNAs; 1.10 Physiological Effects of Loss and Gain of c-myc Function in Mice; 1.10.1 Loss of Function 327 $a1.10.2 Gain of Function: Inducible Transgenic Animals1.11 Contributions of MYC to Tumor Biology; 1.12 Introduction of Hematopoietic Malignancies; 1.13 Mechanisms of MYC Dysregulation in Hematological Malignancies; 1.14 Mutation(s) in the MYC Gene in Hematological Cancers; 1.15 Role of MYC in Cell Cycle Regulation and Differentiation in Hematological Cancers; 1.16 Role of BCR Signaling in Conjunction with MYC Overexpression in Lymphoid Malignancies; 1.17 Deregulation of Auxiliary Proteins in Addition to MYC in Hematological Cancers; 1.18 Conclusion; References 327 $a2 Cancer Stem Cells - Finding and Capping the Roots of Cancer2.1 Introduction - Stem Cells and Cancer Stem Cells; 2.1.1 What are Stem Cells?; 2.1.2 Concept of Cancer Stem Cells (CSCs); 2.2 Hematopoietic Stem Cells as a Paradigm; 2.2.1 Leukemia as a Paradigmatic Disease for Cancer Research; 2.2.2 CFUs; 2.2.3 LTC-ICs; 2.2.4 In Vivo Repopulation; 2.2.5 Importance of the Bone Marrow Niche; 2.2.6 Leukemic Stem Cells; 2.2.6.1 Leukemic Stem Cells in the Bone Marrow Niche; 2.2.7 CML as a Paradigmatic Entity; 2.3 Current Technical Approach to the Isolation and Characterization of Cancer Stem Cells 327 $a2.3.1 Tools for the Detection of Cancer Stem Cells2.3.2 Phenotype of Cancer Stem Cells; 2.4 Cancer Stem Cells in Solid Tumors; 2.4.1 Breast Cancer; 2.4.2 Prostate Cancer; 2.4.3 Colon Cancer; 2.4.4 Other Cancers; 2.5 Open Questions of the Cancer Stem Cell Hypothesis; 2.6 Clinical Relevance of Cancer Stem Cells; 2.6.1 Diagnostic Relevance of Cancer Stem Cells; 2.6.2 Therapeutic Relevance - New Drugs Directed Against Cancer Stem Cells; 2.7 Outlook; References; 3 Multiple Testing Methods; 3.1 Introduction; 3.1.1 A Brief More Focused Introduction; 3.1.2 Historic Development of the Field 327 $a3.2 Statistical Background3.2.1 Tests; 3.2.2 Test Statistics and p-Values; 3.2.3 Resampling Based Testing; 3.3 Type I Error Rates; 3.4 Introduction to Multiple Testing Procedures; 3.4.1 Adjusted p-values; 3.4.2 Categories of Multiple Testing Procedures; 3.4.3 Estimation of the Proportion of False Nulls; 3.5 Multiple Testing Procedures; 3.5.1 Procedures Controlling the FWER; 3.5.2 Procedures Controlling the FDR; 3.5.3 Procedures Controlling the FDX Figure; 3.6 Type I Error Rates Control Under Dependence; 3.6.1 FWER Control; 3.6.2 FDR and FDX Control 327 $a3.7 Multiple Testing Procedures Applied to Gene Discovery in DNA Microarray Cancer Studies 330 $aA collection of highly valuable statistical and computational approaches designed for developing powerful methods to analyze large-scale high-throughput data derived from studies of complex diseases. Such diseases include cancer and cardiovascular disease, and constitute the major health challenges in industrialized countries. They are characterized by the systems properties of gene networks and their interrelations, instead of individual genes, whose malfunctioning manifests in pathological phenotypes, thus making the analysis of the resulting large data sets particularly challenging. This is 606 $aMedicine$xResearch$xStatistical methods 606 $aMedical statistics 615 0$aMedicine$xResearch$xStatistical methods. 615 0$aMedical statistics. 676 $a610.72721 676 $a614.4015195 701 $aEmmert-Streib$b Frank$0867728 701 $aDehmer$b Matthias$0860612 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910876527903321 996 $aMedical biostatistics for complex diseases$94190084 997 $aUNINA