Statistical Methods in Molecular Biology /

Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Bang, Heejung. (Editor), Zhou, Xi Kathy. (Editor), van Epps, Heather L. (Editor), Mazumdar, Madhu. (Editor)
Format: eBook
Language:English
Published: Totowa, NJ : Humana Press : Imprint: Humana, 2010.
Edition:1st ed. 2010.
Series:Methods in Molecular Biology, 620
Subjects:
Table of Contents:
  • 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.