Statistical Methods in Molecular Biology

652 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

Basic Statistics.- Experimental Statistics for Biological Sciences.- Nonparametric Methods for Molecular Biology.- Basics of Bayesian Methods.- The Bayesian t-Test and Beyond.- Designs and Methods for Molecular Biology.- Sample Size and Power Calculation for Molecular Biology Studies.- Designs for Linkage Analysis and Association Studies of Complex Diseases.- to Epigenomics and Epigenome-Wide Analysis.- Exploration, Visualization, and Preprocessing of High-Dimensional Data.- Statistical Methods for Microarray Data.- to the Statistical Analysis of Two-Color Microarray Data.- Building Networks with Microarray Data.- Advanced or Specialized Methods for Molecular Biology.- Support Vector Machines for Classification: A Statistical Portrait.- An Overview of Clustering Applied to Molecular Biology.- Hidden Markov Model and Its Applications in Motif Findings.- Dimension Reduction for High-Dimensional Data.- to the Development and Validation of Predictive Biomarker Models from High-Throughput Data Sets.- Multi-gene Expression-based Statistical Approaches to Predicting Patients' Clinical Outcomes and Responses.- Two-Stage Testing Strategies for Genome-Wide Association Studies in Family-Based Designs.- Statistical Methods for Proteomics.- Meta-Analysis for High-Dimensional Data.- Statistical Methods for Integrating Multiple Types of High-Throughput Data.- A Bayesian Hierarchical Model for High-Dimensional Meta-analysis.- Methods for Combining Multiple Genome-Wide Linkage Studies.- Other Practical Information.- Improved Reporting of Statistical Design and Analysis: Guidelines, Education, and Editorial Policies.- Stata Companion.

• Reihe: Methods in Molecular Biology
• Themen: Mathematik und Naturwissenschaften Biologie, Biowissenschaften Biowissenschaften, allgemein DV-gestützte Biologie/Bioinformatik
• ISBN: 9781493961245
• Sprache: Englisch
• Erscheinungsdatum: 23.08.2016
• Größe: 254 x 178 mm
• Verlag: Humana
• Herausgegeben von: Xi Kathy Zhou, Madhu Mazumdar, Heejung Bang, Heather L. van Epps