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[null,"1.","Record Nr.",null,"UNINA9910140591203321"]
[null,null,"Titolo",null,"Statistical bioinformatics [[electronic resource] ] : a guide for life and biomedical science researchers / / edited by Jae K. Lee"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, NJ, : Wiley, c2010"]
[null,null,"ISBN",null,"1-118-21152-9"]
[{"$nulls":4},"1-282-69036-1"]
[{"$nulls":4},"9786612690365"]
[{"$nulls":4},"0-470-56764-3"]
[{"$nulls":4},"0-470-56763-5"]
[null,null,"Descrizione fisica",null,"1 online resource (386 p.)"]
[null,null,"Disciplina",null,"570.285"]
[null,null,"Soggetti",null,"Bioinformatics - Statistical methods"]
[{"$nulls":4},"Biology - Data processing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"STATISTICAL BIOINFORMATICS; CONTENTS; PREFACE; CONTRIBUTORS; 1 ROAD TO STATISTICAL BIOINFORMATICS; 2 PROBABILITY CONCEPTS AND DISTRIBUTIONS FOR ANALYZING LARGE BIOLOGICAL DATA; 3 QUALITY CONTROL OF HIGH-THROUGHPUT BIOLOGICAL DATA; 4 STATISTICAL TESTING AND SIGNIFICANCE FOR LARGE BIOLOGICAL DATA ANALYSIS; 5 CLUSTERING: UNSUPERVISED LEARNING IN LARGE BIOLOGICAL DATA; 6 CLASSIFICATION: SUPERVISED LEARNING WITH HIGH-DIMENSIONAL BIOLOGICAL DATA; 7 MULTIDIMENSIONAL ANALYSIS AND VISUALIZATION ON LARGE BIOMEDICAL DATA; 8 STATISTICAL MODELS, INFERENCE, AND ALGORITHMS FOR LARGE BIOLOGICAL DATA ANALYSIS"]
[{"$nulls":4},"9 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"]
[null,null,null,"Sommario/riassunto","This 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 "]
[{"$nulls":4},"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"]