Biostatistical methods / edited by Stephen W. Looney.

Contributor(s): Looney, Stephen W
Material type: TextTextSeries: Methods in molecular biology (Clifton, N.J.): v. 184.Publisher: Totowa, N.J. : Humana Press, ©2002Description: 1 online resource (xii, 214 pages) : illustrations (some color)Content type: text Media type: computer Carrier type: online resourceISBN: 9781592592425; 0585428611; 9780585428611; 1592592422; 1280830425; 9781280830426; 9786610830428; 6610830428Subject(s): Biometry | Molecular biology | Biometry -- methods | Biostatistics -- methods | Molecular Biology -- methods | NATURE -- Reference | SCIENCE -- Life Sciences -- General | SCIENCE -- Life Sciences -- Biology | Biometry | Molecular biology | Statistiek | Wetenschappelijke techniekenGenre/Form: Electronic books. Additional physical formats: Print version:: Biostatistical methods.DDC classification: 570/.1/5195 LOC classification: QH323.5 | .B5628 2002ebOther classification: 42.11 Online resources: Click here to access online
Contents:
Statistical Contributions to Molecular Biology / Emmanuel N. Lazaridis, Gregory C. Bloom -- Linking Image Quantitation and Data Analysis / Gregory C. Bloom, Peter Gieser, Emmanuel N. Lazaridis -- Introduction to Microarray Experimentation and Analysis / Peter Gieser, Gregory C. Bloom, Emmanuel N. Lazaridis -- Statistical Methods for Proteomics / Francoise Seiller-Moiseiwitsch, Donald C. Trost, Julian Moiseiwitsch -- Statistical Methods for Assessing Biomarkers / Stephen W. Looney -- Power and Sample Size Considerations in Molecular Biology / L. Jane Goldsmith -- Models for Determining Genetic Susceptibility and Predicting Outcome / Peter W. Jones [and others] -- Multiple Tests for Genetic Effects in Association Studies / Peter H. Westfall, Dmitri V. Zaykin, S. Stanley Young -- Statistical Considerations in Assessing Molecular Markers for Cancer Prognosis and Treatment Efficacy / James Dignam, John Bryant, Soonmyung Paik -- Power of the Rank Test for Multi-Strata Case-Control Studies with Ordinal Exposure Variables / Grzegorz A. Rempala, Stephen W. Looney.
Action note: digitized 2010 committed to preserve In: Springer ProtocolsSummary: The use of biostatistical techniques in molecular biology has grown tremendously in recent years and is now essential for the correct interpretation of a wide variety of laboratory studies. In Biostatistical Methods, a panel of leading biostatisticians and biomedical researchers describe all the key techniques used to solve commonly occurring analytical problems in molecular biology, and demonstrate how these methods can identify new markers for exposure to a risk factor, or for determining disease outcomes. Major areas of application include microarray analysis, proteomic studies, image quantitation, determining new disease biomarkers, and designing studies with adequate levels of statistical power. In the case of genetic effects in human populations, the authors describe sophisticated statistical methods to control the overall false-positive rate when many statistical tests are used in linking particular alleles to the occurrence of disease. Other methods discussed are those used to validate statistical approaches for analyzing the E-D association, to study the associations between disease and the inheritance of particular genetic variants, and to examine real data sets. There are also useful recommendations for statistical and data management software (JAVA, Oracle, S-Plus, STATA, and SAS) . Accessible, state-of-the-art, and highly practical, Biostatistical Methods provides an excellent starting point both for statisticians just beginning work on problems in molecular biology, and for all molecular biologists who want to use biostatistics in genetics research designed to uncover the causes and treatments of disease.
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Includes bibliographical references and index.

Statistical Contributions to Molecular Biology / Emmanuel N. Lazaridis, Gregory C. Bloom -- Linking Image Quantitation and Data Analysis / Gregory C. Bloom, Peter Gieser, Emmanuel N. Lazaridis -- Introduction to Microarray Experimentation and Analysis / Peter Gieser, Gregory C. Bloom, Emmanuel N. Lazaridis -- Statistical Methods for Proteomics / Francoise Seiller-Moiseiwitsch, Donald C. Trost, Julian Moiseiwitsch -- Statistical Methods for Assessing Biomarkers / Stephen W. Looney -- Power and Sample Size Considerations in Molecular Biology / L. Jane Goldsmith -- Models for Determining Genetic Susceptibility and Predicting Outcome / Peter W. Jones [and others] -- Multiple Tests for Genetic Effects in Association Studies / Peter H. Westfall, Dmitri V. Zaykin, S. Stanley Young -- Statistical Considerations in Assessing Molecular Markers for Cancer Prognosis and Treatment Efficacy / James Dignam, John Bryant, Soonmyung Paik -- Power of the Rank Test for Multi-Strata Case-Control Studies with Ordinal Exposure Variables / Grzegorz A. Rempala, Stephen W. Looney.

Print version record.

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Electronic reproduction. [Place of publication not identified] : HathiTrust Digital Library, 2010. MiAaHDL

Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. MiAaHDL

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The use of biostatistical techniques in molecular biology has grown tremendously in recent years and is now essential for the correct interpretation of a wide variety of laboratory studies. In Biostatistical Methods, a panel of leading biostatisticians and biomedical researchers describe all the key techniques used to solve commonly occurring analytical problems in molecular biology, and demonstrate how these methods can identify new markers for exposure to a risk factor, or for determining disease outcomes. Major areas of application include microarray analysis, proteomic studies, image quantitation, determining new disease biomarkers, and designing studies with adequate levels of statistical power. In the case of genetic effects in human populations, the authors describe sophisticated statistical methods to control the overall false-positive rate when many statistical tests are used in linking particular alleles to the occurrence of disease. Other methods discussed are those used to validate statistical approaches for analyzing the E-D association, to study the associations between disease and the inheritance of particular genetic variants, and to examine real data sets. There are also useful recommendations for statistical and data management software (JAVA, Oracle, S-Plus, STATA, and SAS) . Accessible, state-of-the-art, and highly practical, Biostatistical Methods provides an excellent starting point both for statisticians just beginning work on problems in molecular biology, and for all molecular biologists who want to use biostatistics in genetics research designed to uncover the causes and treatments of disease.

English.

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