Mathematical and Statistical Methods for Genetic Analysis

  • Kenneth Lange

Part of the Statistics for Biology and Health book series (SBH)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Kenneth Lange
    Pages 1-20
  3. Kenneth Lange
    Pages 21-38
  4. Kenneth Lange
    Pages 39-58
  5. Kenneth Lange
    Pages 59-79
  6. Kenneth Lange
    Pages 81-96
  7. Kenneth Lange
    Pages 97-114
  8. Kenneth Lange
    Pages 115-139
  9. Kenneth Lange
    Pages 141-168
  10. Kenneth Lange
    Pages 169-201
  11. Kenneth Lange
    Pages 203-229
  12. Kenneth Lange
    Pages 231-255
  13. Kenneth Lange
    Pages 257-280
  14. Kenneth Lange
    Pages 281-297
  15. Kenneth Lange
    Pages 299-316
  16. Kenneth Lange
    Pages 317-339
  17. Back Matter
    Pages 341-369

About this book


During the past decade, geneticists have cloned scores of Mendelian disease genes and constructed a rough draft of the entire human genome. The unprecedented insights into human disease and evolution offered by mapping, cloning, and sequencing will transform medicine and agriculture. This revolution depends vitally on the contributions of applied mathematicians, statisticians, and computer scientists. Mathematical and Statistical Methods for Genetic Analysis is written to equip students in the mathematical sciences to understand and model the epidemiological and experimental data encountered in genetics research. Mathematical, statistical, and computational principles relevant to this task are developed hand in hand with applications to population genetics, gene mapping, risk prediction, testing of epidemiological hypotheses, molecular evolution, and DNA sequence analysis. Many specialized topics are covered that are currently accessible only in journal articles. This second edition expands the original edition by over 100 pages and includes new material on DNA sequence analysis, diffusion processes, binding domain identification, Bayesian estimation of haplotype frequencies, case-control association studies, the gamete competition model, QTL mapping and factor analysis, the Lander-Green-Kruglyak algorithm of pedigree analysis, and codon and rate variation models in molecular phylogeny. Sprinkled throughout the chapters are many new problems.


DNA Factor analysis Haplotype evolution expectation–maximization algorithm genes genetics molecular evolution numerical analysis phylogeny recombination

Authors and affiliations

  • Kenneth Lange
    • 1
  1. 1.Departments of Biomathematics and Human GeneticsUCLA School of MedicineLos AngelesUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag New York 2002
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4684-9556-0
  • Online ISBN 978-0-387-21750-5
  • Series Print ISSN 1431-8776
  • Buy this book on publisher's site