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  • © 2010

Statistical Methods in Molecular Biology

  • An easily accessible reference for statistical methods in molecular miology, written by leading researchers in the field
  • Presents a comprehensive guide to self-learning analysis tools for data generated in molecular biology studies, from basic methods to advanced, specialized methods in a progressive style
  • Details the processing, description/visualization, and analyses of the data and software implementation
  • Covers a wide range of statistical methods for the analyses of various types of data collected in different fields of biological sciences, including standard experimental data and high-dimensional data
  • Includes supplementary material: sn.pub/extras

Part of the book series: Methods in Molecular Biology (MIMB, volume 620)

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Table of contents (23 protocols)

  1. Front Matter

    Pages i-xiii
  2. Basic Statistics

    1. Front Matter

      Pages 1-1
    2. Experimental Statistics for Biological Sciences

      • Heejung Bang, Marie Davidian
      Pages 1-102
    3. Nonparametric Methods for Molecular Biology

      • Knut M. Wittkowski, Tingting Song
      Pages 105-153
    4. Basics of Bayesian Methods

      • Sujit K. Ghosh
      Pages 155-178
    5. The Bayesian t-Test and Beyond

      • Mithat Gönen
      Pages 179-199
  3. Designs and Methods for Molecular Biology

    1. Front Matter

      Pages 201-201
    2. Designs for Linkage Analysis and Association Studies of Complex Diseases

      • Yuehua Cui, Gengxin Li, Shaoyu Li, Rongling Wu
      Pages 219-242
    3. Introduction to Epigenomics and Epigenome-Wide Analysis

      • Melissa J. Fazzari, John M. Greally
      Pages 243-265
  4. Statistical Methods for Microarray Data

    1. Front Matter

      Pages 285-285
    2. Introduction to the Statistical Analysis of Two-Color Microarray Data

      • Martina Bremer, Edward Himelblau, Andreas Madlung
      Pages 287-313
    3. Building Networks with Microarray Data

      • Bradley M. Broom, Waree Rinsurongkawong, Lajos Pusztai, Kim-Anh Do
      Pages 315-343
  5. Advanced or Specialized Methods for Molecular Biology

    1. Front Matter

      Pages 345-345
    2. An Overview of Clustering Applied to Molecular Biology

      • Rebecca Nugent, Marina Meila
      Pages 369-404

About this book

While there is a wide selection of 'by experts, for experts’ books in statistics and molecular biology, there is a distinct need for a book that presents the basic principles of proper statistical analyses and progresses to more advanced statistical methods in response to rapidly developing technologies and methodologies in the field of molecular biology.  Statistical Methods in Molecular Biology strives to fill that gap by covering basic and intermediate statistics that are useful for classical molecular biology settings and advanced statistical techniques that can be used to help solve problems commonly encountered in modern molecular biology studies, such as supervised and unsupervised learning, hidden Markov models, methods for manipulation and analysis of high-throughput microarray and proteomic data, and methods for the synthesis of the available evidences. This detailed volume offers molecular biologists a book in a progressive style where basic statistical methods are introduced and gradually elevated to an intermediate level, while providing statisticians knowledge of various biological data generated from the field of molecular biology, the types of questions of interest to molecular biologists, and the state-of-the-art statistical approaches to analyzing the data.  As a volume in the highly successful Methods in Molecular Biologyâ„¢ series, this work provides the kind of meticulous descriptions and implementation advice for diverse topics that are crucial for getting optimal results.
 
Comprehensive but convenient, Statistical Methods in Molecular Biology will aid students, scientists, and researchers along the pathway from beginning strategies to a deeper understanding of these vital systems of data analysis and interpretation within one concise volume.

 

"Here is a comprehensive book that systematically covers both basic and advanced statistical topics in molecularbiology, including parametric and nonparametric, and frequentist and Bayesian methods.  I am highly impressed by the breadth and depth of the applications. I strongly recommend this book for both statisticians and biologists who need to communicate with each other in this exciting field of research."

- Robert C. Elston, PhD., Director, Division of Genetic and Molecular Epidemiology, Case Western Reserve University

 

"An extraordinary exposition of the central topics of modern molecular biology, presented by practicing experts who weave together rigorous theory with practical techniques and illustrative examples."

- George C. Newman, MD, PhD, Chairman, Neurosensory Sciences, Albert Einstein Medical Center

 

"I cannot think of anything we need now in translation research field more than more efficient cross talk between molecular biology and statistics. This book is just on target. It fills the gap."

- Iman Osman, MB, BCh, MD, Director, Interdisciplinary Melanoma Cooperative Program, New York University Langone Medical Center

Reviews

"Here is a comprehensive book that systematically covers both basic and advanced statistical topics in molecular biology, including parametric and nonparametric, and frequentist and Bayesian methods. I am highly impressed by the breadth and depth of the applications. I strongly recommend this book for both statisticians and biologists who need to communicate with each other in this exciting field of research." (Robert C. Elston, PhD., Director, Division of Genetic and Molecular Epidemiology, Case Western Reserve University)

"An extraordinary exposition of the central topics of modern molecular biology, presented by practicing experts who weave together rigorous theory with practical techniques and illustrative examples." (George C. Newman, MD, PhD, Chairman, Neurosensory Sciences, Albert Einstein Medical Center)

"I cannot think of anything we need now in translation research field more than more efficient cross talk between molecular biology and statistics. This book is just on target. It fills the gap." (Iman Osman, MB, BCh, MD, Director, Interdisciplinary Melanoma Cooperative Program, New York University Langone Medical Center)

Editors and Affiliations

  • Weill Medical College, Dept. Public Health, Cornell University, New York, USA

    Heejung Bang, Xi Kathy Zhou, Madhu Mazumdar

  • Journal of Experimental Medicine, Rockefeller University Press, New York, USA

    Heather L. Epps

Bibliographic Information

Buy it now

Buying options

eBook USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access