00859cam2 22002531 450 SOBE0002534520160215145950.020120514d1827 |||||ita|0103 bafreIT1Milanoper Antonio Fontana1827X, 692 p.20 cm001SOBE000170632001 Storia della guerra della indipendenza degli Stati Uniti di America scritta da Carlo BottaBotta, CarloSOBA00000703070451836ITUNISOB20160215RICAUNISOBUNISOB09474239SOBE00025345M 103 Monografia antica SBNM094000019-1consultabile previa autorizzazioneNO74239acquistobethbUNISOBUNISOB20120514164359.020120514164452.0bethb11717738UNISOB04043nam 22005894a 450 991014575360332120230518151739.01-280-27447-697866102744750-470-01107-60-470-01108-4(CKB)1000000000018874(EBL)210563(OCoLC)209570457(SSID)ssj0000251182(PQKBManifestationID)11204085(PQKBTitleCode)TC0000251182(PQKBWorkID)10245582(PQKB)10725341(MiAaPQ)EBC210563(Au-PeEL)EBL210563(CaPaEBR)ebr10113961(CaONFJC)MIL27447(EXLCZ)99100000000001887420040405d2004 uy 0engur|n|---|||||txtccrStatistics for microarrays[electronic resource] design, analysis, and inference /Ernst Wit and John McClureChichester, England ;Hoboken, NJ, USA John Wiley & Sonsc20041 online resource (279 p.)Description based upon print version of record.0-470-84993-2 Includes bibliographical references (p. 251-258) and index.Contents; Preface; 1 Preliminaries; 1.1 Using the R Computing Environment; 1.1.1 Installing smida; 1.1.2 Loading smida; 1.2 Data Sets from Biological Experiments; 1.2.1 Arabidopsis experiment: Anna Amtmann; 1.2.2 Skin cancer experiment: Nighean Barr; 1.2.3 Breast cancer experiment: John Bartlett; 1.2.4 Mammary gland experiment: Gusterson group; 1.2.5 Tuberculosis experiment: BμG@S group; I: Getting Good Data; 2 Set-up of a Microarray Experiment; 2.1 Nucleic Acids: DNA and RNA; 2.2 Simple cDNA Spotted Microarray Experiment; 3 Statistical Design of Microarrays; 3.1 Sources of Variation3.2 Replication3.3 Design Principles; 3.4 Single-channel Microarray Design; 3.5 Two-channel Microarray Designs; 4 Normalization; 4.1 Image Analysis; 4.2 Introduction to Normalization; 4.3 Normalization for Dual-channel Arrays; 4.4 Normalization of Single-channel Arrays; 5 Quality Assessment; 5.1 Using MIAME in Quality Assessment; 5.2 Comparing Multivariate Data; 5.3 Detecting Data Problems; 5.4 Consequences of Quality Assessment Checks; 6 Microarray Myths: Data; 6.1 Design; 6.2 Normalization; II: Getting Good Answers; 7 Microarray Discoveries; 7.1 Discovering Sample Classes7.2 Exploratory Supervised Learning7.3 Discovering Gene Clusters; 8 Differential Expression; 8.1 Introduction; 8.2 Classical Hypothesis Testing; 8.3 Bayesian Hypothesis Testing; 9 Predicting Outcomes with Gene Expression Profiles; 9.1 Introduction; 9.2 Curse of Dimensionality: Gene Filtering; 9.3 Predicting Class Memberships; 9.4 Predicting Continuous Responses; 10 Microarray Myths: Inference; 10.1 Differential Expression; 10.2 Prediction and Learning; Bibliography; Index; A; B; C; D; E; F; G; H; I; K; L; M; N; O; P; Q; R; S; T; U; V; WInterest in microarrays has increased considerably in the last ten years. This increase in the use of microarray technology has led to the need for good standards of microarray experimental notation, data representation, and the introduction of standard experimental controls, as well as standard data normalization and analysis techniques. Statistics for Microarrays: Design, Analysis and Inference is the first book that presents a coherent and systematic overview of statistical methods in all stages in the process of analysing microarray data - from getting good data to obtaining meaningDNA microarraysStatistical methodsDNA microarraysStatistical methods.629.04Wit Ernst614547McClure John D989215MiAaPQMiAaPQMiAaPQBOOK9910145753603321Statistics for microarrays2262274UNINA