TY - BOOK ID - 1542203 TI - Bioinformatics and Computational Biology Solutions Using R and Bioconductor AU - Gentleman, Robert. AU - Carey, Vincent. AU - Huber, Wolfgang. AU - Irizarry, Rafael. AU - Dudoit, Sandrine. PY - 2005 SN - 0387251464 9780387251462 9786610413409 1280413409 0387293620 PB - New York, NY : Springer New York : Imprint: Springer, DB - UniCat KW - Biomathematics. Biometry. Biostatistics KW - Mathematical statistics KW - Bioinformatics. KW - R (Computer program language) KW - Bio-informatique KW - R (Langage de programmation) KW - Bioconductor (Computer file) KW - Bioinformatics KW - R (Computer program language). KW - Models, Theoretical KW - Statistics as Topic KW - Software KW - Biology KW - Computing Methodologies KW - Epidemiologic Methods KW - Biological Science Disciplines KW - Investigative Techniques KW - Health Care Evaluation Mechanisms KW - Quality of Health Care KW - Natural Science Disciplines KW - Information Science KW - Analytical, Diagnostic and Therapeutic Techniques and Equipment KW - Public Health KW - Health Care Quality, Access, and Evaluation KW - Disciplines and Occupations KW - Environment and Public Health KW - Health Care KW - Models, Statistical KW - Programming Languages KW - Computational Biology KW - Health & Biological Sciences KW - Biology - General KW - EPUB-LIV-FT LIVSTATI SPRINGER-B KW - GNU-S (Computer program language) KW - Bio-informatics KW - Biological informatics KW - Computer science. KW - Animal genetics. KW - Statistics. KW - Computer Science. KW - Computational Biology/Bioinformatics. KW - Statistics for Life Sciences, Medicine, Health Sciences. KW - Animal Genetics and Genomics. KW - Information science KW - Computational biology KW - Systems biology KW - Statistical analysis KW - Statistical data KW - Statistical methods KW - Statistical science KW - Mathematics KW - Econometrics KW - Genetics KW - Informatics KW - Science KW - Data processing KW - Domain-specific programming languages KW - Bioconductor (Computer file). KW - Monograph KW - StatisticsĀ . KW - Computational biology. KW - Genomics. KW - Genetic Techniques. KW - Genetic Techniques KW - Models, statistical KW - Probability UR - https://www.unicat.be/uniCat?func=search&query=sysid:1542203 AB - Bioconductor is a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology. Bioconductor is rooted in the open source statistical computing environment R. This volume's coverage is broad and ranges across most of the key capabilities of the Bioconductor project, including importation and preprocessing of high-throughput data from microarray, proteomic, and flow cytometry platforms curation and delivery of biological metadata for use in statistical modeling and interpretation statistical analysis of high-throughput data, including machine learning and visualization, modeling and visualization of graphs and networks. The developers of the software, who are in many cases leading academic researchers, jointly authored chapters. All methods are illustrated with publicly available data, and a major section of the book is devoted to exposition of fully worked case studies. This book is more than a static collection of descriptive text, figures, and code examples that were run by the authors to produce the text; it is a dynamic document. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers. Robert Gentleman is Head of the Program in Computational Biology at the Fred Hutchinson Cancer Research Center in Seattle. He is one of the two authors of the original R system and a leading member of the R core team. Vincent Carey is Associate Professor of Medicine (Biostatistics), Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School. Gentleman and Carey are co-founders of the Bioconductor project. Wolfgang Huber is Group Leader in the European Molecular Biology Laboratory at the European Bioinformatics Institute in Cambridge. He has made influential contributions to the error modeling of microarray data. Rafael Irizarry is Associate Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health in Baltimore. He is co-developer of RMA and GCRMA, two of the most popular methodologies for preprocessing high-density oligonucleotide arrays. Sandrine Dudoit is Assistant Professor in the Department of Biostatistics at the University of California, Berkeley. She has made seminal discoveries in the fields of multiple testing and generalized cross-validation and spearheaded the deployment of these findings in applied genomic science. ER -