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Leading biostatisticians and biomedical researchers describe many of the key techniques used to solve commonly occurring data analytic problems in molecular biology, and demonstrate how these methods can be used in the development of new markers for exposure to a risk factor or for disease outcomes. Major areas of application include microarray analysis, proteomic studies, image quantitation, genetic susceptibility and association, evaluation of new biomarkers, and power analysis and sample size.

Produktbeschreibung
Leading biostatisticians and biomedical researchers describe many of the key techniques used to solve commonly occurring data analytic problems in molecular biology, and demonstrate how these methods can be used in the development of new markers for exposure to a risk factor or for disease outcomes. Major areas of application include microarray analysis, proteomic studies, image quantitation, genetic susceptibility and association, evaluation of new biomarkers, and power analysis and sample size.

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Rezensionen
"The book presents the reader with a representative sampling of biostatistical applications that are used in the study of molecular biology with an emphasis on the development of biomarkers for clinical applications." - Biotech Software & Internet Report

"In 10 chapters the authors fulfill the aim to provide sufficient information to cover area of both biostatistics and molecular biology...authors pay attention to give accurate explanation of basic biological and statistical terms. This is worthwhile for statisticians who want to work in molecular biology and for molecular biologists to be in touch with recent advances in comprehensive high-throughput laboratory methods." -Neoplasma

"...an excellent overview of the most promising statistical approaches for analyzing microarray data...recommended to be read both by molecular biologists and biostatisticians." - Statist. Med.