LEADER 03340nam 2200613Ia 450 001 9910140591203321 005 20200520144314.0 010 $a1-118-21152-9 010 $a1-282-69036-1 010 $a9786612690365 010 $a0-470-56764-3 010 $a0-470-56763-5 035 $a(CKB)2670000000014706 035 $a(EBL)514371 035 $a(OCoLC)609862656 035 $a(SSID)ssj0000366205 035 $a(PQKBManifestationID)11290379 035 $a(PQKBTitleCode)TC0000366205 035 $a(PQKBWorkID)10414571 035 $a(PQKB)10462620 035 $a(MiAaPQ)EBC514371 035 $a(Au-PeEL)EBL514371 035 $a(CaPaEBR)ebr10383627 035 $a(CaONFJC)MIL269036 035 $a(PPN)186157746 035 $a(EXLCZ)992670000000014706 100 $a20090626d2010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aStatistical bioinformatics$b[electronic resource] $ea guide for life and biomedical science researchers /$fedited by Jae K. Lee 210 $aHoboken, NJ $cWiley$dc2010 215 $a1 online resource (386 p.) 300 $aDescription based upon print version of record. 311 $a0-471-69272-7 320 $aIncludes bibliographical references and index. 327 $aSTATISTICAL BIOINFORMATICS; CONTENTS; PREFACE; CONTRIBUTORS; 1 ROAD TO STATISTICAL BIOINFORMATICS; 2 PROBABILITY CONCEPTS AND DISTRIBUTIONS FOR ANALYZING LARGE BIOLOGICAL DATA; 3 QUALITY CONTROL OF HIGH-THROUGHPUT BIOLOGICAL DATA; 4 STATISTICAL TESTING AND SIGNIFICANCE FOR LARGE BIOLOGICAL DATA ANALYSIS; 5 CLUSTERING: UNSUPERVISED LEARNING IN LARGE BIOLOGICAL DATA; 6 CLASSIFICATION: SUPERVISED LEARNING WITH HIGH-DIMENSIONAL BIOLOGICAL DATA; 7 MULTIDIMENSIONAL ANALYSIS AND VISUALIZATION ON LARGE BIOMEDICAL DATA; 8 STATISTICAL MODELS, INFERENCE, AND ALGORITHMS FOR LARGE BIOLOGICAL DATA ANALYSIS 327 $a9 EXPERIMENTAL DESIGNS ON HIGH-THROUGHPUT BIOLOGICAL EXPERIMENTS10 STATISTICAL RESAMPLING TECHNIQUES FOR LARGE BIOLOGICAL DATA ANALYSIS; 11 STATISTICAL NETWORK ANALYSIS FOR BIOLOGICAL SYSTEMS AND PATHWAYS; 12 TRENDS AND STATISTICAL CHALLENGES IN GENOMEWIDE ASSOCIATION STUDIES; 13 R AND BIOCONDUCTOR PACKAGES IN BIOINFORMATICS: TOWARDS SYSTEMS BIOLOGY; INDEX 330 $aThis book provides an essential understanding of statistical concepts necessary for the analysis of genomic and proteomic data using computational techniques. The author presents both basic and advanced topics, focusing on those that are relevant to the computational analysis of large data sets in biology. Chapters begin with a description of a statistical concept and a current example from biomedical research, followed by more detailed presentation, discussion of limitations, and problems. The book starts with an introduction to probability and statistics for genome-wide data, and moves into 606 $aBioinformatics$xStatistical methods 606 $aBiology$xData processing 615 0$aBioinformatics$xStatistical methods. 615 0$aBiology$xData processing. 676 $a570.285 701 $aLee$b Jae K$0901228 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910140591203321 996 $aStatistical bioinformatics$92014283 997 $aUNINA